Index
A
- absorbing / How to do it...
- adaptive histogram equalization
- reference link / There's more...
- adjacency list
- about / Graphs
- adjacency matrix
- about / Graphs
- advanced image processing algorithms
- reference link / References
- advanced optimization methods, image processing
- reference link / References
- air resistance
- reference / There's more...
- allreduce() function / How it works…
- alternative parallel computing solutions
- alternative parallel computing solutions, Python
- references / References
- Anaconda distribution
- URL / Getting ready
- analog signal
- about / Analog and digital signals
- annotations
- about / How it works…
- Anti-Grain Geometry
- API reference, InteractiveShell
- URL / There's more...
- API reference, skimage.feature module
- reference link / There's more...
- API reference, skimage.filter module
- link / There's more...
- API reference, skimage.morphology module
- link / There's more...
- architecture, IPython notebook
- about / Architecture of the IPython notebook
- multiple clients, connecting to kernel / Connecting multiple clients to one kernel
- array buffers
- about / How it works…
- array computations
- accelerating, with Numexpr / Accelerating array computations with Numexpr, How it works...
- array interface, NumPy
- URL / There's more...
- arrays
- manipulating, with HDF5 / Manipulating large arrays with HDF5 and PyTables, How to do it..., How it works...
- manipulating, with PyTables / Manipulating large arrays with HDF5 and PyTables, How to do it..., How it works...
- array selections
- making, in NumPy / Making efficient array selections in NumPy, How to do it...
- array views
- assert-like functions, NumPy
- reference / How it works...
- asynchronous parallel tasks
- interacting with / Interacting with asynchronous parallel tasks in IPython, How to do it…, How it works…
- AsyncResult, attributes
- elapsed / How it works…
- progress / How it works…
- serial_time / How it works…
- metadata / How it works…
- AsyncResult, methods
- ready() / How it works…
- successful() / How it works…
- wait() / How it works…
- get() / How it works…
- AsyncResult class
- URL, for documentation / There's more…
- as_strided method / How it works...
- ATLAS / Why are NumPy arrays efficient?
- attribute / How it works…
- attributes, InteractiveShell class
- user_ns / The InteractiveShell class
- audio filters
- reference link / There's more...
- audio signal processing
- reference link / References, There's more...
- augmented matrix
- about / How to do it...
- autocorrelation
- computing, of time series / Computing the autocorrelation of a time series, How to do it..., How it works...
- reference / There's more...
- autocorrelation function, statsmodels
- reference / There's more...
- AutoHotKey
- URL / How to do it…
- AutoHotKey script, in Windows Explorer
- URL / How to do it…
- AutoIt
- URL / How to do it…
- automated testing
- about / Writing unit tests with nose
- AVX / Why are NumPy arrays efficient?
B
- B-tree
- about / There's more...
- bagging
- ball trees
- about /
- band-pass filter
- about / The low-, high-, and band-pass filters
- reference / There's more...
- bandlimited
- Basemap
- URL / References, Getting ready
- basemap
- about / Getting ready, Manipulating geospatial data with Shapely and basemap
- geospatial data, manipulating with / How to do it…
- batch rendering / There's more…
- Bayes' theorem / How to do it..., Bayes' theorem
- Bayesianism
- URL, for blog / Frequentist and Bayesian methods
- Bayesian method
- about / Frequentist and Bayesian methods
- Bayesian methods
- overview / How to do it..., How it works...
- computation, of posterior distribution / Computation of the posterior distribution
- posteriori estimation, maximizing / Maximum a posteriori estimation
- reference / There's more...
- Bayesians
- Bayesian theory
- Bazaar
- about / Getting ready
- benchmarking / Profiling your code easily with cProfile and IPython
- Bernoulli distribution
- reference / How to do it...
- Bernoulli Naive Bayes classifier
- about /
- bias
- bias-variance dilemma
- bias-variance tradeoff
- about / How it works...
- reference / How it works...
- bifurcation diagram
- plotting, of chaotic dynamical system / Plotting the bifurcation diagram of a chaotic dynamical system, How to do it...
- about / Plotting the bifurcation diagram of a chaotic dynamical system
- Bifurcation diagrams
- reference / There's more...
- Bifurcation theory
- reference link / There's more...
- binary installer, Chris Gohlke's webpage
- URL / Getting ready
- Binomial distribution
- reference / How to do it...
- Birnbaum-Sanders distribution
- about / How to do it...
- reference / How to do it...
- bisect() function / How to do it…
- Bisection method
- reference link / There's more…
- bisection method
- about / How to do it…
- Bitbucket
- about / Getting ready
- bivariate method
- BLAS / Why are NumPy arrays efficient?
- Blaze
- URL / There's more..., There's more…
- about / Introduction, How it works…
- Blinn-Phong shading model
- about / How it works…
- URL / How it works…
- block
- about / How it works…
- blocking mode
- about / How to do it…
- Bokeh
- about / Creating interactive web visualizations with Bokeh
- used, for creating interactive web visualizations / Getting ready, How to do it…
- URL / Getting ready
- references / There's more…
- Bokeh figures
- about / There's more…
- Boolean propositional formula
- finding, from truth table / Finding a Boolean propositional formula from a truth table, How to do it...
- Boosting
- reference link / There's more...
- bootstrap aggregating
- boundary condition / Differential equations
- branches
- references / There's more…
- branching
- Brent's method
- about / How to do it…
- reference link / There's more…
- brentq() method / How to do it…
- broadcasting
- about / How to do it...
- broadcasting rules
- about / How to do it..., What are NumPy broadcasting rules?
- reference / There's more...
- Brownian motion
- about / Simulating a Brownian motion
- simulating / Simulating a Brownian motion, How to do it..., How it works...
- references / There's more...
- Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm / How to do it…
- bus factor
- references / How it works…
- Butterworth filter
C
- %%cython cell magic
- about / There's more…
- calculus
- about / Analyzing real-valued functions
- references / There's more...
- Canopy distribution
- URL / Getting ready
- Canvas / How to do it…
- cardinal sine
- about / How to do it…
- CART
- about / How it works...
- cartopy
- Cartopy
- URL / References
- cascade classification API reference, OpenCV
- reference link / There's more...
- cascade tutorial, OpenCV (C++)
- reference link / There's more...
- causal filters / Linear filters and convolutions
- cdef keyword
- about / How it works…
- cells
- about / How to do it..., How it works…
- cellular automata
- reference / There's more...
- cellular automaton
- about / Types of dynamical systems
- Census Bureau website
- reference link / How to do it…
- cffi
- references / There's more…
- Chaos theory
- reference / There's more...
- reference link / There's more...
- chaotic dynamical system
- about / Plotting the bifurcation diagram of a chaotic dynamical system
- bifurcation diagram, plotting of / Plotting the bifurcation diagram of a chaotic dynamical system, How to do it...
- chi-squared test
- chi-square test
- used, for estimating correlation between variables / Estimating the correlation between two variables with a contingency table and a chi-squared test, How to do it...
- about / How to do it...
- Chi2 test, SciPy documentation
- URL / There's more...
- Chinese Remainder Theorem
- about / How it works...
- references / There's more...
- Chi square test
- reference / There's more...
- Chromatic scale
- URL / There's more...
- chunks
- about / There's more...
- chunk shape
- about / There's more...
- classical graph problems
- examples / Problems in graph theory
- classification
- about / Supervised learning
- examples / Supervised learning
- C library
- wrapping, with ctypes / Wrapping a C library in Python with ctypes, Getting ready, How to do it…, How it works…
- clustering
- about / Unsupervised learning, Detecting hidden structures in a dataset with clustering
- hidden structures, detecting in dataset / Detecting hidden structures in a dataset with clustering, How to do it..., How it works...
- references / There's more...
- clusters
- CMA-ES algorithm
- reference link / There's more…
- coalesces
- about / How it works…
- code
- writing / Writing code that works in Python 2 and Python 3
- debugging, with IPython / Debugging your code with IPython, How to do it...
- profiling, cProfile used / Profiling your code easily with cProfile and IPython, How to do it..., How it works...
- profiling, IPython used / Profiling your code easily with cProfile and IPython, How to do it..., How it works..., There's more...
- profiling, with line_profiler / Profiling your code line-by-line with line_profiler, How do to it..., There's more...
- parallelizing, with MPI / Parallelizing code with MPI in IPython, How to do it…, How it works…
- code cells
- about / How to do it...
- code coverage
- references / There's more...
- code debugging, with IPython
- post-mortem mode / The post-mortem mode
- step-by-step debugging mode / Step-by-step debugging
- coin tossing experiment / How it works...
- column-major order
- command mode
- about / What's new in IPython 2.0?
- command prompt
- about / Getting ready
- commit
- about / How it works…
- Comms / How it works...
- compilation, with Cython
- URL / There's more…
- compiler-related installation instructions
- about / Compiler-related installation instructions
- Linux / Linux
- Mac OS X / Mac OS X
- Windows / Windows
- complex systems
- reference / There's more...
- components / Learning from data
- compressed sensing
- about / Compressed sensing, How it works...
- references / Compressed sensing
- Computer-Aided Design (CAD)
- about / How it works…
- concurrent programming
- conda
- about / How to do it…, How to do it...
- conditional probability distribution
- about / Bayes' theorem
- Configurable class
- about / How it works...
- example / Configurables
- configuration file
- about / How it works...
- configuration object
- about / How it works...
- configuration system, IPython
- mastering / Mastering IPython's configuration system, How to do it...
- user profile / How it works...
- configuration object / How it works...
- HasTraits class / How it works...
- Configurable class / How it works...
- configuration file / How it works...
- conjugate distributions
- about / Conjugate distributions
- reference / Conjugate distributions
- connected-component labeling
- about / How it works…
- connected component labeling
- reference link / There's more…
- connected components
- about / Computing connected components in an image, How it works…
- computing, in image / Computing connected components in an image, How to do it…, How it works…
- reference link / There's more…
- connected components, graphs
- reference link / Problems in graph theory
- connected graph
- about / Graphs
- constrained optimization
- constrained optimization algorithm
- about / How to do it…
- contiguous block
- about / How it works..., There's more...
- contingency table
- used, for estimating correlation between variables / Estimating the correlation between two variables with a contingency table and a chi-squared test, How to do it...
- about / How to do it..., Contingency table and chi-squared test
- reference / There's more...
- Continuous-time process
- reference / There's more...
- continuous functions
- about / The objective function
- continuous integration
- references / There's more...
- about / Unit testing and continuous integration
- continuous integration systems
- continuous optimization
- about / Introduction
- Continuum Analytics
- Contrast
- reference link / There's more...
- Contrast Limited Adaptive Histogram Equalization (CLAHE) / How to do it...
- conversion examples, nbconvert
- URL / There's more...
- convex functions
- about / The objective function
- convex optimization
- about / The objective function
- reference link / References
- convolution
- about / Linear filters and convolutions
- convolutions
- references / There's more...
- Conway's Game of Life
- about / There's more...
- reference / There's more...
- corner detection
- reference link / There's more...
- corner detection example, scikit-image
- reference link / There's more...
- corner_harris() function
- about / How to do it...
- corner_peaks() function
- about / How to do it..., How it works...
- correlation
- reference / How to do it...
- correlation function
- reference / There's more...
- counting process / How to do it...
- course, Computational Fluid Dynamics
- URL / References, There's more...
- Covariance Matrix Adaptation Evolution Strategy (CMA-ES) algorithm
- about / How it works…
- coverage module
- about / Test coverage
- coveralls.io service
- about / Test coverage
- cProfile
- used, for profiling code / Profiling your code easily with cProfile and IPython, How to do it..., How it works...
- URL, for documentation / There's more...
- CPython
- CRAN
- URL / There's more...
- credible interval
- about / Credible interval
- reference / Credible interval
- cross-validation
- about / How to do it..., Cross-validation and grid search, Predicting who will survive on the Titanic with logistic regression
- reference link / There's more…
- grid search, performing with / Getting ready, How to do it..., How it works...
- CSS
- references / There's more...
- CSS style
- customizing, in notebook / Customizing the CSS style in the notebook, How to do it...
- CSV (Comma-separated values) / How to do it...
- ctypes
- about / Introduction, Wrapping a C library in Python with ctypes
- used, for wrapping C library / Wrapping a C library in Python with ctypes, Getting ready, How to do it…, How it works…
- ctypes module
- CUDA
- massively parallel code, writing for NVIDIA graphics cards (GPUs) / Writing massively parallel code for NVIDIA graphics cards (GPUs) with CUDA, Getting ready, How to do it..., How it works…
- about / Writing massively parallel code for NVIDIA graphics cards (GPUs) with CUDA
- references / There's more…
- CUDA cores
- about / How it works…
- CUDA programming model
- kernel / How it works…
- thread / How it works…
- block / How it works…
- grid / How it works…
- CUDA SDK
- URL / Getting ready
- cumulative distribution function
- about / How it works...
- cumulative distribution function (CDF)
- about / How to do it...
- cumulative time / How it works...
- curvefit
- reference documentation / There's more…
- curve fitting
- about / How to do it…
- curve fitting regression problem
- about / How to do it...
- curve_fit() function
- about / How to do it…
- custom controls
- adding, in notebook toolbar / Adding custom controls in the notebook toolbar, How to do it..., There's more...
- custom JavaScript widget
- creating, for notebook / Creating a custom JavaScript widget in the notebook – a spreadsheet editor for pandas, How to do it..., How it works...
- custom magic commands
- IPython extension, creating with / Creating an IPython extension with custom magic commands, How to do it..., How it works...
- cutoff frequency
- cvtColor() function / How to do it...
- Cython
- about / Introduction, Accelerating Python code with Cython
- Python code, accelerating with / Accelerating Python code with Cython, How to do it…, How it works…
- URL, for installing / Getting ready
- Cython, installing on Windows
- URL / References
- Cython, installing on Windows 64-bit
- URL / References
- Cython code
- integrating, within Python package / There's more…
- optimizing / Optimizing Cython code by writing less Python and more C, How to do it…, How it works…
- Cython extension types
- URL / There's more…
- Cython modules
- URL / There's more…
D
- %debug magic command / The post-mortem mode
- D3.js
- URL / Visualizing a NetworkX graph in the IPython notebook with D3.js
- about / Visualizing a NetworkX graph in the IPython notebook with D3.js
- NetworkX graph, visualizing with / Visualizing a NetworkX graph in the IPython notebook with D3.js, How to do it…
- references / There's more…
- D3.js visualizations
- matplotlib figures, converting to / How to do it…, How it works…
- data
- data buffer / Why are NumPy arrays efficient?
- data buffers
- vertex buffers / How it works…
- index buffers / How it works…
- textures / How it works…
- data dimensions
- observations / Univariate and multivariate methods
- variables / Univariate and multivariate methods
- data manipulation, Pandas
- references / There's more...
- data point / Learning from data
- dataset
- exploring, with pandas / Exploring a dataset with pandas and matplotlib, How to do it...
- exploring, with matplotlib / Exploring a dataset with pandas and matplotlib, How to do it...
- dimensionality, reducing with principal component analysis (PCA) / Reducing the dimensionality of a dataset with a principal component analysis, How to do it..., How it works...
- hidden structures, detecting in / Detecting hidden structures in a dataset with clustering, How to do it..., How it works...
- datasets
- about / How it works...
- data structures, for graphs
- reference link / References
- data type
- about / How it works...
- datautils package
- about / Test coverage
- data visualization
- debugger
- references / Step-by-step debugging
- debugging
- about / Debugging your code with IPython
- decisions trees
- decision theory
- deep learning
- reference link / Machine learning references
- defensive programming
- about / How to do it...
- degree of belief
- about / Frequentist and Bayesian methods
- Delaunay triangulation
- about / How it works…
- reference link / There's more…
- denoise_tv_bregman() function
- about / How it works...
- dependencies
- about / There's more…
- functional dependency / Dependent parallel tasks
- graph dependency / Dependent parallel tasks
- Dependency Walker
- URL / DLL hell
- dependent parallel tasks / Dependent parallel tasks
- descartes
- descartes package
- about / Geometry in Python
- design patterns
- about / How to do it...
- deterministic algorithm
- deterministic dynamical systems
- about / Types of dynamical systems
- discrete-time dynamical systems / Types of dynamical systems
- cellular automaton / Types of dynamical systems
- Ordinary Differential Equations (ODEs) / Types of dynamical systems
- Partial Differential Equations (PDEs) / Types of dynamical systems
- development version, Vispy
- reference / Getting ready
- difference equation
- about / The FIR and IIR filters
- differentiable functions
- about / The objective function
- differential equations
- about / Differential equations
- Diffusion process
- reference / There's more...
- digital filters
- applying, to speech sounds / How to do it…, How it works...
- digital signal
- about / Analog and digital signals, How it works...
- sampling rate / Analog and digital signals
- resolution / Analog and digital signals
- linear filters, applying to / Getting ready, How to do it...
- digital signal processing
- references / There's more...
- Dijkstra's algorithm
- about / How it works…
- reference link / There's more…
- dilation / How it works...
- dimensionality / Learning from data
- direct acyclic graph (DAG)
- about / How it works...
- directed acyclic graph
- dependencies, resolving with topological sort / Resolving dependencies in a directed acyclic graph with a topological sort, How to do it…
- directed acyclic graphs
- about / There's more…
- reference link / There's more…
- directed graph
- about / Graphs
- direct interface / How it works…
- discrete-time dynamical system
- about / Types of dynamical systems
- discrete-time Markov chain
- about / Simulating a discrete-time Markov chain
- simulating / How to do it...
- discrete-time signal / Analog and digital signals
- discrete convolution / How it works...
- Discrete Fourier Transform (DFT)
- about / The Discrete Fourier Transform
- discrete optimization
- about / Introduction
- distributed version control system
- DLL Hell
- about / DLL hell
- document classification example, scikit-learn
- reference link /
- DRAM (Dynamic Random Access Memory)
- about / How it works…
- draw_spectral() function
- about / There's more…
- draw_spring() function
- about / There's more…
- Dynamically Linked Libraries (DLLs)
- dynamical systems
- references / References
- reference link / There's more...
- Dynamical Systems
- reference link / There's more...
E
- Eclipse/PyDev
- edges
- about / Graphs
- edit mode
- about / What's new in IPython 2.0?
- ego graph / How to do it…
- elastic potential energy / How it works…
- reference link / There's more…
- elementary cellular automata
- reference / There's more...
- elementary cellular automaton
- about / Simulating an elementary cellular automaton
- simulating / How to do it..., How it works...
- elements, in rendering pipeline of OpenGL
- data buffers / How it works…
- variables / How it works…
- shaders / How it works…
- primitive type / How it works…
- embarrassingly parallel problem / There's more...
- empirical distribution function
- about / How to do it...
- energy() function / How it works…
- engines output printing, in real-time
- reference / There's more…
- ensemble learning
- equalize_adapthist() function / How it works...
- Equal temperament
- URL / There's more...
- equations
- solving / Getting ready, How to do it...
- equations, SymPy
- reference link / LaTeX
- equilibrium points
- about / How it works...
- equilibrium points, Scholarpedia
- reference link / There's more...
- equilibrium state, of physical system
- finding, by minimizing potential energy / Finding the equilibrium state of a physical system by minimizing its potential energy, How to do it…, How it works…
- erosion / How it works...
- ESRI shapefile
- estimation
- Euler-Maruyama method
- about / Simulating a stochastic differential equation
- reference / There's more...
- Eulerian paths
- reference link / Problems in graph theory
- Euler method
- about / How it works...
- reference / There's more...
- exact probabilities
- computing / How to do it..., How it works...
- examples, classification
- handwritten digit recognition / Supervised learning
- spam filtering / Supervised learning
- expectation-maximization algorithm
- about / How it works...
- reference link / There's more...
- exploratory data analysis, IPython / Getting started with exploratory data analysis in IPython, How to do it...
- exploratory methods
- exponential distribution
- reference / How to do it...
- extended version, ray tracing engine
- URL / There's more…
- extension system, IPython
- URL, for documentation / There's more...
- extrema
- reference link / References
- extremum
- about / The objective function
F
- Fast Fourier Transform (FFT)
- about / Analyzing the frequency components of a signal with a Fast Fourier Transform
- used, for analyzing frequency components of signal / Analyzing the frequency components of a signal with a Fast Fourier Transform, How to do it..., How it works...
- feature / Learning from data
- feature extraction
- features, for regression
- selecting, random forests used / Using a random forest to select important features for regression, How to do it..., How it works...
- feature scaling
- feature selection
- about / Feature selection and feature extraction
- references / Feature selection and feature extraction
- feedback term / The FIR and IIR filters
- feedforward term / The FIR and IIR filters
- FFmpeg
- URL / Getting ready
- fftfreq() utility / How to do it...
- filters
- applying, on image / Applying filters on an image, How it works..., How it works...
- filters, frequency domain
- about / Filters in the frequency domain
- Finite Impulse Response (FIR) filter
- about / The FIR and IIR filters
- references / There's more...
- Fiona
- URL / References, Getting ready
- FIR filter
- about / How to do it...
- FitzHugh-Nagumo equation
- FitzHugh-Nagumo system
- references / There's more...
- fit_transform() method / How to do it...
- fixtures
- about / How it works...
- flood-fill algorithm
- about / How it works…
- reference link / There's more…
- FLOPS
- fluid dynamics
- about / Types of dynamical systems
- Fokker-Planck equation
- about / How it works...
- reference / There's more...
- Folium
- URL / References
- force-directed graph drawing
- reference link / There's more…
- forking
- about / There's more…
- Fourier transform
- Fourier transforms
- references / There's more...
- fragment shader
- about / How to do it…
- frequency components, signal
- analyzing, with Fast Fourier Transform (FFT) / Analyzing the frequency components of a signal with a Fast Fourier Transform, How to do it..., How it works...
- frequentism
- URL, for blog / Frequentist and Bayesian methods
- frequentist method
- about / Frequentist and Bayesian methods
- URL, for classic misuses / Frequentist and Bayesian methods
- frequentist methods, hypothesis testing / How to do it...
- frequentists
- Fruchterman-Reingold force-directed algorithm
- about / There's more…
- function, fitting to data
- nonlinear least squares used / How to do it…, How it works…
- functional dependency
- about / Dependent parallel tasks
- fundamental frequency
- about / How it works...
G
- Gaussian filter
- about / How it works...
- reference link / There's more...
- Gaussian kernel
- about / How it works...
- GCC (GNU Compiler Collection)
- about / Linux
- GDAL/OGR
- geographical distances
- reference link / There's more…
- Geographical Information Systems / Geographical Information Systems in Python
- Geographic Information Systems (GIS)
- about / Introduction
- geometry
- references / References
- GeoPandas
- about / Geographical Information Systems in Python
- URL / References
- geospatial data
- manipulating, with Shapely / How to do it…
- manipulating, with basemap / How to do it…
- get_config() function / Configurables
- ggplot, for Python
- URL / There's more…
- ggplot2
- URL / There's more…
- GIL
- reference / CPython and concurrent programming
- Git
- about / Getting ready, How it works…
- references / There's more…
- git-flow / There's more…
- git branch command / How to do it…
- Git branching
- workflow / Getting ready, How to do it…, How it works…
- git diff command / How to do it…
- GitHub
- about / Getting ready
- git log command / How to do it…
- Gitorious
- about / Getting ready
- git remote add command / Cloning a remote repository
- git status command / How to do it…
- Global Interpreter Lock (GIL)
- global minimum
- about / Local and global minima
- glue language
- Goodness of fit
- reference / There's more...
- Google code
- about / Getting ready
- GPGPU
- gradient
- reference link, for definition / There's more…
- gradient descent / How it works…
- graph-tool
- about / Graphs in Python
- graph-tool package
- reference link / References
- graph coloring
- reference link / Problems in graph theory
- graph dependency
- about / Dependent parallel tasks
- Graphics Processing Units (GPUs)
- graphs
- about / Introduction, Graphs
- vertices / Graphs
- nodes / Graphs
- edges / Graphs
- references / References
- manipulating, with NetworkX / How to do it…
- visualizing, with NetworkX / How to do it…
- graph theory
- reference link / References
- graph traversal
- reference link / Problems in graph theory
- GraphViz
- URL / How it works...
- gravitational force / How it works…
- grayscale image
- about / Images
- great-circle distance / How it works…
- Great circle
- reference link / There's more…
- Great circle distance
- reference link / There's more…
- grid
- about / How it works…
- grid search
- about / Cross-validation and grid search, Predicting who will survive on the Titanic with logistic regression
- reference link / There's more…
- performing, with cross-validation / Getting ready, How to do it..., How it works...
- Gross Domestic Product (GDP)
- groups
- about / How it works...
- GUI debuggers
- about / GUI debuggers
- GUI on Mac OS X / Getting ready
- GUI on Windows / Getting ready
- Guppy-PE
- URL / Other tools
H
- 44100 Hz sampling rate
- reference link / References
- h5py
- about / Manipulating large arrays with HDF5 and PyTables
- URL / There's more...
- references / There's more...
- Haar cascades library
- reference link / There's more...
- Hamiltonian paths
- reference link / Problems in graph theory
- Handsontable JavaScript library
- handwritten digit recognition / Supervised learning
- handwritten digits
- recognizing, K-nearest neighbors (K-NN) classifier used /
- Harris corner measure response image / How to do it...
- Harris matrix / How it works...
- Hartman-Grobman theorem
- about / How it works...
- HasTraits class
- about / How it works...
- HDF5
- arrays, manipulating with / Manipulating large arrays with HDF5 and PyTables, How to do it..., How it works...
- about / Manipulating large arrays with HDF5 and PyTables
- heterogeneous tables, manipulating with / How to do it..., How it works...
- HDF5 chunking
- references / There's more...
- heat equation
- about / How it works...
- Hessian / How it works…
- heterogeneous computing
- heterogeneous platforms
- massively parallel code, writing for / Writing massively parallel code for heterogeneous platforms with OpenCL, Getting ready, How to do it…, How it works…
- heterogeneous tables
- manipulating, with PyTables / Getting ready, How to do it..., How it works...
- manipulating, with HDF5 / Getting ready, How to do it..., How it works...
- hidden structures
- detecting, in dataset / Detecting hidden structures in a dataset with clustering, How to do it..., How it works...
- high-level plotting interfaces
- references / There's more…
- high-pass filter
- about / The low-, high-, and band-pass filters
- reference / There's more...
- high-quality Python code
- histogram / How to do it...
- histogram equalization
- reference link / There's more...
- holding times / How it works...
- Hooke's law
- reference link / There's more…
- hubs
- about / Random graphs
- hyperbolic
- about / How it works...
I
- IDEs
- IDEs, for Python
- links / There's more...
- IHaskell / What is the notebook?
- IJulia / What is the notebook?
- IJulia package
- about / Introduction
- URL / Trying the Julia language in the notebook
- image
- filters, applying on / Applying filters on an image, How it works..., How it works...
- segmenting / Segmenting an image, How to do it..., How it works...
- points of interest, finding in / How to do it..., How it works...
- connected components, computing in / Computing connected components in an image, How to do it…, How it works…
- image denoising / How it works...
- reference link / There's more...
- image exposure
- manipulating / Manipulating the exposure of an image, How to do it..., How it works...
- image histogram
- reference link / There's more...
- image processing
- reference link / References
- image processing, SciPy lecture notes
- reference link / There's more...
- image processing tutorial, scikit-image
- reference link / There's more...
- images
- about / Images
- image segmentation
- reference link / There's more...
- Impermium Kaggle challenge
- reference link /
- implicit-copy operations
- versus in-place operations / What is the difference between in-place and implicit-copy operations?
- impulse responses
- references / There's more...
- in-kernel queries
- about / How it works...
- references / There's more...
- in-place operations
- versus implicit-copy operations / What is the difference between in-place and implicit-copy operations?
- independent variables
- about / Types of dynamical systems
- index, IPython extensions
- URL / There's more...
- indexing routines
- URL / There's more...
- inequalities
- solving / Getting ready, How to do it...
- Infinite Impulse Response (IIR) filter
- about / The FIR and IIR filters
- references / There's more...
- initial condition / Differential equations
- instance-based learning
- example /
- reference link /
- integrate package, SciPy
- URL, for documentation / There's more...
- Intel Math Kernel Library (MKL) / Why are NumPy arrays efficient?
- intensity / Images
- interactive computing workflow, IPython
- InteractiveShell class
- about / The InteractiveShell class
- attributes / The InteractiveShell class
- methods / The InteractiveShell class
- interactive web visualizations
- creating, with Bokeh / Getting ready, How to do it…
- interactive widgets
- interest point detection
- reference link / There's more...
- intermediate value theorem
- about / How it works…
- reference link / There's more…
- Inverse Discrete Fourier Transform
- about / Inverse Fourier Transform
- Inverse Fast Fourier Transform
- about / Inverse Fourier Transform
- inverse FFT
- about / How to do it...
- Inverse Fourier Transform
- about / Inverse Fourier Transform
- ipycache
- about / How to do it…
- IPython
- about / What is IPython?, The IPython terminal
- URL, for installation instructions / Getting ready
- URL / Getting ready
- exploratory data analysis / Getting started with exploratory data analysis in IPython, How to do it...
- configuration system, mastering / Mastering IPython's configuration system, How to do it...
- references / There's more...
- kernel, creating for / Creating a simple kernel for IPython, How to do it..., How it works...
- interactive computing workflows / Efficient interactive computing workflows with IPython
- using, with text editor / IPython and text editor
- code, debugging with / Debugging your code with IPython, How to do it...
- embedding, within program / There's more...
- time, evaluating by statement / How it works...
- used, for profiling code / Profiling your code easily with cProfile and IPython, How to do it..., How it works..., There's more...
- %memit magic command, using in / Using the %memit magic command in IPython
- Python code, distributing across multiple cores / How to do it…, How it works…
- interacting, with asynchronous parallel tasks / Interacting with asynchronous parallel tasks in IPython, How to do it…, How it works…
- code, parallelizing with MPI / Parallelizing code with MPI in IPython, How to do it…, How it works…
- NetworkX graph, visualizing with D3.js / Visualizing a NetworkX graph in the IPython notebook with D3.js, How to do it…
- IPython-text editor workflow
- about / IPython and text editor
- IPython.parallel
- references / References
- IPython 2.0
- modifications, over v1.1 / What's new in IPython 2.0?
- about / The notebook ecosystem
- IPython blocks
- used, for teaching programming in notebook / Teaching programming in the notebook with IPython blocks, How to do it...
- IPython Blocks
- IPython documentation
- IPython engines / How it works…
- IPython extension
- creating, with custom magic commands / Creating an IPython extension with custom magic commands, How to do it..., How it works...
- about / How to do it...
- loading / Loading an extension
- IPython notebook
- overview / Introducing the IPython notebook, Getting ready, How to do it...
- about / The IPython notebook
- architecture / Architecture of the IPython notebook
- converting to other formats, with nbconvert / Converting an IPython notebook to other formats with nbconvert, How to do it..., How it works...
- data analyzing, with R programming language / Analyzing data with the R programming language in the IPython notebook, Getting ready, How to do it..., How it works...
- IPython notebook examples
- reference / What's new in IPython 2.0?
- IPython terminal
- about / The IPython terminal
- IPython tutorial
- reference / There's more...
- Iris flower data set
- reference link / There's more…
- IRuby / What is the notebook?
- iterated functions
- reference / There's more...
- iteritems() method / Writing code that works in Python 2 and Python 3
- Itō calculus
- reference / There's more...
J
- Jacobian matrix
- about / How it works...
- Joblib
- about / How to do it…
- joblib
- JSON
- JSON on Wikipedia
- URL / There's more...
- Julia
- about / Introduction, Trying the Julia language in the notebook
- URL / Trying the Julia language in the notebook
- URL, for packages / Getting ready
- strengths / There's more…
- Julia language
- trying, in notebook / How to do it…
- references / There's more…
- Julia tutorial, SciPy 2014 conference
- Jupyter
- about / What is the notebook?
- URL / What is the notebook?
- Just-In-Time compilation
- Python code, accelerating with / Accelerating pure Python code with Numba and just-in-time compilation, How to do it…, How it works…
- Just-In-Time compilation (JIT)
- about / Introduction
K
- K-D trees
- about /
- K-means algorithm
- about / How to do it...
- reference link / There's more...
- K-nearest neighbors (K-NN) classifier
- about /
- handwritten digits, recognizing with /
- references /
- Kaggle
- Kartograph
- about / Geographical Information Systems in Python
- URL / References
- KDE implementations, scikit-learn
- reference / How it works...
- KDE implementations, statsmodels
- reference / How it works...
- kernel
- creating, for IPython / Creating a simple kernel for IPython, How to do it..., How it works...
- multiple clients, connecting to / Connecting multiple clients to one kernel
- about / How it works…, How it works...
- KernelBase API
- reference / There's more...
- kernel density estimation (KDE)
- used, for estimating probability distribution nonparametrically / Estimating a probability distribution nonparametrically with a kernel density estimation, How to do it..., How it works...
- about / Estimating a probability distribution nonparametrically with a kernel density estimation
- kernel density estimator
- about / How it works...
- reference / How it works...
- kernels
- about / What is IPython?, How to do it...
- kernel spec / How to do it...
- kernel trick
- about / How it works...
- kernprof file
- URL, for downloading / There's more...
- Khronos Group
- Kolmogorov-Smirnov test
- about / How to do it...
- reference / There's more...
L
- %lprun command
- about / How it works...
- L-BFGS-B algorithm
- about / How to do it…
- reference link / There's more…
- L2 norm
- lambdify() function / How to do it...
- Langevin equation
- about / Simulating a stochastic differential equation
- reference / There's more...
- LAPACK / Why are NumPy arrays efficient?
- Laplacian matrix
- about / There's more…
- LaTeX
- about / How to do it..., LaTeX
- references / LaTeX
- LaTeX distribution
- reference / Getting ready
- LaTeX equations
- about / How to do it...
- least squares method
- reference / There's more...
- references / There's more…
- Leave-One-Out cross-validation
- about / Cross-validation and grid search
- left singular vectors
- about / How it works...
- Levenberg-Marquardt algorithm / How it works…
- reference link / There's more…
- linear algebra
- references / There's more...
- linear combination / How it works...
- linear filters
- about / Applying a linear filter to a digital signal, What are linear filters?
- applying, to digital signal / Getting ready, How to do it...
- and convolutions / Linear filters and convolutions
- references / There's more...
- linear system / Differential equations
- Linear Time-Invariant (LTI)
- about / What are linear filters?
- line_profiler
- used, for profiling code / Profiling your code line-by-line with line_profiler, How do to it..., There's more...
- URL / Profiling your code line-by-line with line_profiler
- Linux
- about / Linux
- Lloyd's algorithm / How it works...
- LLVM (Low Level Virtual Machine)
- about / How it works…
- lm() function / How it works...
- load-balanced interface / How it works…
- Locality of reference
- URL / There's more...
- locality of reference / Why are NumPy arrays efficient?
- local minimum
- about / Local and global minima
- local repository
- creating / Creating a local repository
- logistic map
- about / Plotting the bifurcation diagram of a chaotic dynamical system
- reference / There's more...
- logistic regression
- about / Predicting who will survive on the Titanic with logistic regression
- references / There's more...
- loss function
- Lotka-Volterra equations
- low-pass filter
- about / The low-, high-, and band-pass filters
- reference / There's more...
- Lyapunov exponent
- Lévi function
- about / How to do it…
M
- %memit magic command
- using, in IPython / Using the %memit magic command in IPython
- machine learning
- about / Introduction
- references / Introduction, Machine learning references
- Mac OS X
- about / Mac OS X
- magic commands
- about / How to do it...
- cythonmagic / There's more...
- rmagic / There's more...
- octavemagic / There's more...
- URL / There's more...
- magic function
- about / The InteractiveShell class
- Magics class
- about / Magics
- mandelbrot() function
- about / How to do it…, How to do it…
- size argument / How it works…, How to do it...
- iterations argument / How it works…, How to do it...
- pointer argument / How it works…, How to do it...
- manually-vectorized code
- Numba, comparing with / There's more…
- manual testing
- about / Writing unit tests with nose
- MAP
- reference / Maximum a posteriori estimation
- Maple
- maps
- references / References
- Markdown
- about / How to do it...
- URL / How to do it…
- Markdown cell
- about / How to do it...
- Markov Chain
- Markov chain Monte Carlo (MCMC)
- about / How it works...
- Markov chain Monte Carlo method
- reference / There's more...
- Markov Chain Monte Carlo method
- Bayesian model, fitting by sampling from posterior distribution / Fitting a Bayesian model by sampling from a posterior distribution with a Markov chain Monte Carlo method, How to do it..., How it works...
- Markov chains
- about / Introduction
- references / There's more...
- Markov property
- about / Introduction
- reference / References
- Mathematica
- mathematical function
- root, finding of / How to do it…, How it works…
- minimizing / Minimizing a mathematical function, How to do it…, How it works…
- mathematical morphology / How it works...
- reference link / There's more...
- mathematical optimization
- about / Introduction
- reference link / References
- mathematical optimization, SciPy
- reference link / References, There's more…
- MathJax
- matplotlib
- about / A brief historical retrospective on Python as a scientific environment, Making nicer matplotlib figures with prettyplotlib
- URL, for installation instructions / Getting ready
- references, for improving styling / There's more…
- dataset, exploring with / Exploring a dataset with pandas and matplotlib, How to do it...
- matplotlib figures
- improving, with prettyplotlib / How to do it…, How it works…
- converting, to D3.js visualizations / How to do it…, How it works…
- matrix
- about / How it works...
- Matrix documentation, SymPy
- URL / There's more..., There's more...
- maxima
- reference link / References
- maximum, of function
- about / Local and global minima
- maximum a posteriori (MAP)
- about / Maximum a posteriori estimation
- maximum likelihood estimate
- about / How to do it...
- reference / There's more...
- maximum likelihood method
- about / Fitting a probability distribution to data with the maximum likelihood method
- used for fitting, probability distribution to data / How to do it..., How it works...
- memoize pattern
- about / How to do it…
- memory mapping
- about / Processing huge NumPy arrays with memory mapping, Manipulating large arrays with HDF5 and PyTables
- NumPy arrays, processing with / Processing huge NumPy arrays with memory mapping, How it works...
- memory mapping, arrays
- about / Introduction
- memory usage, of code
- profiling, with memory_profiler / Profiling the memory usage of your code with memory_profiler, How to do it...
- memory_profiler
- memory usage of code, profiling with / Profiling the memory usage of your code with memory_profiler, How to do it...
- URL, for downloading / Profiling the memory usage of your code with memory_profiler
- memory_profiler package
- about / How it works...
- using, for standalone Python programs / Using memory_profiler for standalone Python programs
- Mercurial
- about / Getting ready
- merge
- about / How it works…
- merging
- about / How it works…
- messaging protocols
- reference / There's more...
- Metaheuristics for function minimization
- reference link / There's more…
- methods, InteractiveShell class
- push() / The InteractiveShell class
- ev() / The InteractiveShell class
- ex() / The InteractiveShell class
- run_cell() / The InteractiveShell class
- safe_execfile() / The InteractiveShell class
- system() / The InteractiveShell class
- write() / The InteractiveShell class
- write_err() / The InteractiveShell class
- register_magic_function() / The InteractiveShell class
- Metropolis-Hastings algorithm
- Milstein method
- reference / There's more...
- MinGW
- URL / Python 32-bit
- minima
- reference link / References
- minimize() function / How to do it…
- minimize_scalar() function / How to do it…
- minimum, of function
- about / Local and global minima
- modal user interface
- about / What's new in IPython 2.0?
- Model-View-Controller (MVC) / How it works...
- model selection
- about / Model selection
- reference link / Model selection
- Monte-Carlo methods
- references / There's more...
- Monte Carlo method / There's more...
- moving average method
- MPI
- about / Parallelizing code with MPI in IPython
- code, parallelizing with / Parallelizing code with MPI in IPython, How to do it…, How it works…
- references, for tutorials / How it works…
- mpi4py package
- URL / Getting ready
- MPICH
- URL / Getting ready
- mpld3 library
- about / Converting matplotlib figures to D3.js visualizations with mpld3
- URL, for installation instructions / Getting ready
- matplotlib figures, converting to D3.js visualizations / How to do it…, How it works…
- mpld3, GitHub
- URL / There's more…
- mplexporter
- URL / There's more…
- mplexporter framework
- about / How it works…
- msysGit
- URL / Getting ready
- multi-core processors
- advantage, taking of / Releasing the GIL to take advantage of multicore processors with Cython and OpenMP, How to do it…
- multidimensional array
- multidimensional array, NumPy
- for fast array computations / Introducing the multidimensional array in NumPy for fast array computations, How to do it..., How it works..., There's more...
- multiple clients
- connecting, to kernel / Connecting multiple clients to one kernel
- multiprocessing module
- multiprocessors
- about / How it works…
- multivariate method
N
- 100 NumPy exercises
- URL / There's more...
- Naive Bayes classifier
- references /
- Natural Earth
- Navier-Stokes equations
- about / Differential equations
- reference / References
- nbconvert
- about / There's more...
- URL / There's more...
- used, for converting IPython notebook to other format / Converting an IPython notebook to other formats with nbconvert, How to do it..., How it works...
- URL, for documentation / There's more...
- nbviewer
- about / There's more...
- URL / There's more...
- reference / There's more...
- NetworkX
- about / Graphs in Python
- URL, for installation instructions / Getting ready
- graphs, manipulating with / How to do it…
- graphs, visualizing with / How to do it…
- social network, analyzing with / Analyzing a social network with NetworkX, How to do it…
- NetworkX graph
- visualizing, with D3.js / Visualizing a NetworkX graph in the IPython notebook with D3.js, How to do it…
- NetworkX package
- reference link / References
- Neumann boundary conditions
- about / How to do it...
- references / There's more...
- Newton's method
- about / How it works…
- reference link / There's more…, There's more…
- Newton's second law of motion
- about / How it works...
- reference / There's more...
- NLTK
- URL /
- nodes
- about / Graphs
- nogil keyword / How it works…
- noise reduction
- reference link / There's more...
- non-contiguous
- about / How to do it...
- non-informative prior distributions
- non-Python languages, notebook
- references / References
- nonlinear differential system
- analyzing / Getting ready, How to do it..., How it works...
- nonlinear least squares
- used, for fitting function to data / How to do it…, How it works…
- reference link / There's more…
- nonlinear least squares curve fitting
- nonlinear system / Differential equations
- nonparametric estimation
- nonparametric model
- nose
- unit tests, writing with / Writing unit tests with nose, How to do it..., How it works...
- URL, for documentation / How it works...
- notebook
- about / What is IPython?, What is the notebook?
- contents / There's more...
- references / There's more...
- URL, for blog / What is the notebook?
- security / Security in notebooks
- programming, teaching with IPython blocks / Teaching programming in the notebook with IPython blocks, How to do it...
- CSS style, customizing in / Getting ready, How to do it...
- custom JavaScript widget, creating for / Creating a custom JavaScript widget in the notebook – a spreadsheet editor for pandas, How to do it..., How it works...
- webcam images, processing from / Processing webcam images in real time from the notebook, How to do it..., How it works...
- Julia language, trying in / How to do it…
- sound synthesizer, creating in / Creating a sound synthesizer in the notebook, How it works...
- notebook architecture
- references / References
- notebook ecosystem
- about / The notebook ecosystem
- notebook toolbar
- custom controls, adding in / Adding custom controls in the notebook toolbar, How to do it..., There's more...
- Notebook widgets
- about / What's new in IPython 2.0?
- null hypothesis
- about / How to do it...
- Numba
- about / Introduction, Accelerating pure Python code with Numba and just-in-time compilation
- URL / Accelerating pure Python code with Numba and just-in-time compilation
- Python code, accelerating with / Accelerating pure Python code with Numba and just-in-time compilation, How to do it…, How it works…
- comparing, with manually-vectorized code / There's more…
- references / There's more…
- number theory
- references / There's more...
- number theory, SymPy / How to do it..., How it works...
- references / There's more...
- numerical methods, ODEs
- reference / There's more...
- Numexpr
- about / Introduction, How it works…, Accelerating array computations with Numexpr
- array computations, accelerating with / Accelerating array computations with Numexpr, How it works...
- URL, for installation instructions / Getting ready
- NumPy
- about / A brief historical retrospective on Python as a scientific environment, Introducing the multidimensional array in NumPy for fast array computations, Introduction
- references / There's more...
- unnecessary array copying, avoiding / Understanding the internals of NumPy to avoid unnecessary array copying, How to do it...
- stride tricks, using with / Using stride tricks with NumPy, How to do it..., How it works...
- efficient array selections, making in / Making efficient array selections in NumPy, How to do it...
- NumPy, Travis Oliphant
- URL / Introduction
- numpy.ctypeslib module
- NumPy arrays
- about / Why are NumPy arrays efficient?
- features / Why are NumPy arrays efficient?
- processing, with memory mapping / Processing huge NumPy arrays with memory mapping, How it works...
- NumPy optimization
- about / Introduction
- NumPy routines
- URL / There's more...
- NVIDIA graphics cards (GPUs)
- massively parallel code, writing for / Writing massively parallel code for NVIDIA graphics cards (GPUs) with CUDA, Getting ready, How to do it..., How it works…
- Nyquist-Shannon sampling theorem
- about / The Nyquist–Shannon sampling theorem
- reference / The Nyquist–Shannon sampling theorem
- Nyquist criterion
- Nyquist frequency
- Nyquist rate
O
- OAuth authentication codes / Getting ready
- objective function
- about / The objective function
- observation / Learning from data
- observations / Univariate and multivariate methods
- odeint() function / How it works...
- ODEPACK
- about / How it works...
- ODEPACK package, FORTRAN
- reference / There's more...
- ODEs
- about / Types of dynamical systems
- reference / There's more...
- offset
- about / Getting ready
- Online Python Tutor
- OpenCL
- about / Writing massively parallel code for NVIDIA graphics cards (GPUs) with CUDA
- references / There's more…
- massively parallel code, writing for heterogeneous platforms / Writing massively parallel code for heterogeneous platforms with OpenCL, Getting ready, How to do it…, How it works…
- resources / There's more…
- OpenCL compute unit / How it works…
- OpenCL NDRange / How it works…
- OpenCL SDKs
- references / Getting ready
- OpenCL work groups / How it works…
- OpenCL work items / How it works…
- OpenCV
- URL / Introduction
- about / Introduction, Detecting faces in an image with OpenCV
- faces, detecting in image / Detecting faces in an image with OpenCV, How to do it..., How it works...
- references / Getting ready
- OpenGL / How it works…
- OpenGL ES 2.0 / How it works…
- OpenGL Program / How to do it…
- OpenGL Shading Language (GLSL) / How it works…
- OpenGL viewport
- about / How to do it…
- OpenMP
- OpenStreetMap
- URL / References
- OpenStreetMap service
- order
- about / Differential equations
- ordinary differential equation
- simulating, with SciPy / Simulating an ordinary differential equation with SciPy, How to do it..., How it works...
- Ordinary Differential Equations (ODEs)
- ordinary least squares regression
- Ornstein-Uhlenbeck process / Simulating a stochastic differential equation
- reference / There's more...
- orthodromic distance / How it works…
- Otsu's method
- reference link / There's more...
- out-of-core computations
- output areas
- about / How to do it...
- overfitting / Supervised learning
P
- %%prun cell magic
- about / How to do it...
- %pdb on command / The post-mortem mode
- %prun line magic
- about / How to do it...
- %px* magic commands / How it works…
- @pyimport macro / How to do it…
- p-value
- about / How it works...
- packaging
- about / How to do it...
- Pandas
- about / A brief historical retrospective on Python as a scientific environment, There's more...
- URL, for installation instructions / Getting ready
- pandas
- dataset, exploring with / Exploring a dataset with pandas and matplotlib, How to do it...
- about / There's more...
- pandoc
- URL, for documentation / Getting ready
- ParallelPython
- parameter vector
- parametric estimation method
- parametric method
- partial derivatives
- about / Types of dynamical systems
- partial differential equation
- Partial Differential Equations (PDEs)
- partition
- about / Supervised learning
- pcolormesh() function / How to do it…
- PDEs
- about / Types of dynamical systems
- Pearson's correlation coefficient
- about / Pearson's correlation coefficient
- reference / Pearson's correlation coefficient
- PEP8
- about / How to do it...
- pep8 package
- about / How to do it...
- phi / How it works...
- pickle module / How to do it…
- Pillow
- URL, for installing / Getting ready
- point process
- about / How to do it..., Simulating a Poisson process
- reference / There's more...
- point processes
- about / Introduction
- points of interest
- about / Finding points of interest in an image
- finding, in image / How to do it..., How it works...
- point sprites
- Poisson process
- about / How to do it..., Simulating a Poisson process
- simulating / How to do it..., How it works...
- reference / There's more...
- polynomial interpolation, linear regression / Polynomial interpolation with linear regression
- posterior distribution
- about / How to do it...
- potential energy
- reference link / There's more…
- power spectral density (PSD)
- prediction
- premature optimization / "Premature optimization is the root of all evil"
- preprocessing
- prettyplotlib
- about / Making nicer matplotlib figures with prettyplotlib
- URL, for installation instructions / Getting ready
- used, for improving matplotlib figures / How to do it…, How it works…
- prime-counting function
- about / How to do it...
- prime number theorem
- about / How to do it...
- primitive assembly / How it works…
- primitive type
- about / How it works…
- principal component analysis (PCA)
- used, for reducing dataset dimensionality / Reducing the dimensionality of a dataset with a principal component analysis, How to do it..., How it works...
- about / Reducing the dimensionality of a dataset with a principal component analysis
- reference link / There's more…
- principal components
- principle of minimum energy
- reference link / There's more…
- principle of minimum total potential energy / How it works…
- prior probability distribution
- probabilistic model
- probability distribution, fitting to data
- maximum likelihood method used / How to do it..., How it works...
- probability distribution nonparametrically
- estimating, with kernel density estimation / Estimating a probability distribution nonparametrically with a kernel density estimation, Getting ready, How to do it..., How it works...
- probability mass function (PMF)
- about / How to do it...
- probit model
- about / Supervised learning
- reference link / Supervised learning
- profiling / Profiling your code easily with cProfile and IPython
- profiling, Python scripts
- reference / There's more...
- profiling tools, Python
- URL / There's more...
- program optimization
- reference / "Premature optimization is the root of all evil"
- Project Jupyter
- about / What is IPython?
- propositional formula
- reference / There's more...
- propositional formulas
- pstats
- URL, for documentation / There's more...
- psutil
- URL / Getting ready
- PTVS
- pull request
- about / There's more…
- pure tone
- about / How it works...
- reference link / There's more...
- PyAudio
- URL / There's more...
- PyCharm
- PyCUDA
- PyCUDA wiki
- URL / Getting ready
- pydot
- about / How it works...
- pydub package
- URL, for downloading / Getting ready
- Pylint
- URL / How to do it...
- PyMC package
- PyMC tutorial
- reference / There's more...
- Pympler
- URL / Other tools
- PyOpenCL
- pyplot
- PyPy
- URL / Introduction
- about / Introduction
- PyPy, Travis Oliphant
- URL / Introduction
- PySizer
- URL / Other tools
- PyTables
- arrays, manipulating with / Manipulating large arrays with HDF5 and PyTables, How to do it..., How it works...
- about / Manipulating large arrays with HDF5 and PyTables
- URL, for installation / Getting ready
- references / There's more...
- heterogeneous tables, manipulating with / How to do it..., How it works...
- Python
- references / References
- URL / Getting ready
- about / Introduction
- Python(x,y) distribution
- URL / Getting ready
- Python, as scientific environment
- historical retrospective / A brief historical retrospective on Python as a scientific environment
- references / A brief historical retrospective on Python as a scientific environment
- Python, interfacing with C
- URL / Introduction
- python-apt package
- URL / Getting ready
- python-graph
- about / Graphs in Python
- python-graph package
- reference link / References
- Python 2
- about / Getting ready, Choosing (or not) between Python 2 and Python 3
- versus Python 3 / Main differences in Python 3 compared to Python 2
- references / There's more...
- Python 2, or Python 3
- selecting between / Python 2 or Python 3?
- options, for selecting / There's more...
- Python 2.x
- about / Python 64-bit
- Python 3
- about / Getting ready, Choosing (or not) between Python 2 and Python 3
- versus Python 2 / Main differences in Python 3 compared to Python 2
- references / There's more...
- Python 3.x
- about / Python 64-bit
- Python 32-bit
- about / Python 32-bit
- Python 64-bit
- about / Python 64-bit
- PythonAnywhere
- Python code
- accelerating, with Numba / Accelerating pure Python code with Numba and just-in-time compilation, How to do it…, How it works…
- accelerating, with Just-In-Time compilation / Accelerating pure Python code with Numba and just-in-time compilation, How to do it…, How it works…
- accelerating, with Cython / Accelerating Python code with Cython, How to do it…, How it works…
- distributing, across multiple cores with IPython / How to do it…, How it works…
- Python implementation, of CMA-ES
- reference link / There's more…
- Python package
- about / Loading an extension
- Cython code, integrating within / There's more…
- Python program
- step-by-step execution, tracing / Tracing the step-by-step execution of a Python program
- Python Tools for Visual Studio
- URL / Getting ready
- Python wheels, for Windows 64-bit
- URL / References
- Python wrapper
- references / Getting ready
Q
- Qhull
- about / How it works…
- URL / There's more…
- quantified signal / Analog and digital signals
- quasi-Newton methods
- about / How it works…
- Quasi-Newton methods
- reference link / There's more…
- Quine-McCluskey algorithm
- about / How it works...
- URL / There's more...
R
- %run magic command / IPython and text editor, How to do it...
- R
- URL / Analyzing data with the R programming language in the IPython notebook
- about / Analyzing data with the R programming language in the IPython notebook
- used, for analyzing data / Analyzing data with the R programming language in the IPython notebook, Getting ready, How to do it..., How it works...
- references / There's more...
- Rackspace
- URL / There's more...
- Radial Basis Function (RBF)
- about / How to do it...
- Random Access Memory (RAM) / Why are NumPy arrays efficient?
- random forests
- about / Using a random forest to select important features for regression
- used, for selecting features for regression / Using a random forest to select important features for regression, How to do it..., How it works...
- references / There's more...
- random graphs
- about / Random graphs
- reference link / References
- random subspace method
- about / How it works...
- random variable
- about / How to do it...
- random variables
- manipulating / How to do it..., How it works...
- random walk
- about / Simulating a Brownian motion
- rasterization / How it works…
- RATP
- reference link / Getting ready
- Ray tracing
- reference / How it works…
- reachability relation
- about / How it works…
- reaction-diffusion system
- reaction-diffusion systems
- references / There's more...
- Read-Evaluate-Print Loop (REPL) / Architecture of the IPython notebook
- real-valued functions
- analyzing / How to do it...
- real analysis
- references / There's more...
- rebasing
- about / How it works…
- red, green, and blue (RGB) / Images
- regionprops() function
- about / How to do it...
- regions
- about / How it works…
- regression
- about / Supervised learning
- examples / Supervised learning
- regression analysis
- reference / There's more...
- regressions
- about / How it works...
- regularization
- remote repository
- cloning / Cloning a remote repository
- render() function / How it works...
- rendering pipeline
- about / How it works…
- working / How it works…
- Renewal theory
- reference / There's more...
- REPL
- reproducible interactive computing experiments
- about / Ten tips for conducting reproducible interactive computing experiments
- tips, for conducting / How to do it…, How it works…
- references / There's more...
- requests module
- reference / How to do it...
- rescale_intensity() function / How it works...
- reStructuredText (reST)
- about / How to do it…
- ridge regression
- about / How to do it..., Ridge regression
- reference link / Ridge regression
- ridge regression model
- about / How to do it...
- drawback / Cross-validation and grid search
- road network
- route planner, creating for / Creating a route planner for a road network, How to do it…, How it works…
- robust model
- rolling average / Implementing an efficient rolling average algorithm with stride tricks
- rolling average algorithm
- implementing, with stride tricks / Implementing an efficient rolling average algorithm with stride tricks, How to do it...
- rolling mean
- about / How to do it...
- root
- finding, of mathematical function / How to do it…, How it works…
- root finding course, SciPy
- reference link / There's more…
- route planner
- creating, for road network / Creating a route planner for a road network, How to do it…, How it works…
- row-major order
- rpy2
- URL, for downloading / Getting ready
- R tutorial
- reference / There's more...
- Rule 110 automaton
- about / How it works...
- reference / There's more...
- RunSnakeRun
- about / There's more...
- URL / There's more...
S
- saddle point
- about / How to do it...
- Sage
- about / A brief historical retrospective on Python as a scientific environment, Introduction, Getting started with Sage
- URL / Getting started with Sage
- URL, for installing / Getting ready
- references / There's more...
- Sage notebook
- creating / How to do it...
- Sage notebooks
- reference / Getting ready
- sample / Learning from data
- sample mean
- about / How it works...
- samples / Univariate and multivariate methods
- scatter() function / How to do it...
- scene graph
- scientific visualization, Vispy / Vispy for scientific visualization
- scikit-image
- about / Introduction
- URL / Introduction
- URL, for installation instructions / Getting ready
- scikit-learn
- text data, handling /
- scikit-learn package
- about / Introduction
- URL / Getting started with scikit-learn
- overview / Getting started with scikit-learn, How to do it...
- URL, for installing / Getting ready
- API / The scikit-learn API
- fit() method / The scikit-learn API
- predict() method / The scikit-learn API
- references / There's more…
- SciPy
- about / A brief historical retrospective on Python as a scientific environment
- ordinary differential equation, simulating with / Simulating an ordinary differential equation with SciPy, How to do it..., How it works...
- scipy.optimize module
- reference manual / References
- about / How to do it…, How to do it…
- references / There's more…, There's more…
- scipy.spatial.voronoi module
- reference link, for documentation / There's more…
- seaborn
- statistical plots, creating with / Creating beautiful statistical plots with seaborn, How to do it…
- about / Creating beautiful statistical plots with seaborn
- URL, for installation instructions / Getting ready
- security, notebooks / Security in notebooks
- segmentation tutorial, scikit-image
- reference link / There's more...
- self.send_response() method
- IOPub socket / How it works...
- message type / How it works...
- sequential locality / Why are NumPy arrays efficient?
- serial dependence
- reference / There's more...
- shader composition system
- shaders
- about / How to do it…
- vertex shaders / How it works…
- fragment shaders / How it works…
- shape, array / How it works...
- Shapefile
- Shapely
- about / Geometry in Python, Manipulating geospatial data with Shapely and basemap
- URL / References, Getting ready
- geospatial data, manipulating with / How to do it…
- shortest paths
- reference link / Problems in graph theory, There's more…
- shortest_path() function / How to do it…
- shortest_path function / How it works…
- sigmoid function
- about / How it works...
- signal processing
- references / References
- signals
- about / Introduction
- analog / Analog and digital signals
- digital / Analog and digital signals
- SIMD paradigm
- SimpleCV
- URL / Introduction
- simulated annealing algorithm
- about / How it works…
- reference link / There's more…
- simulated annealing method
- about / How to do it…
- Single Instruction, Multiple Data (SIMD) / Understanding the internals of NumPy to avoid unnecessary array copying
- about / There's more…
- Singular Value Decomposition (SVD)
- about / How it works...
- singular values
- about / How it works...
- six module
- small-world graphs
- reference link / References
- small-world networks
- about / Random graphs
- Sobel filter / How it works...
- reference link / There's more...
- social data analysis, Python
- reference / There's more…
- social network
- analyzing, with NetworkX / Analyzing a social network with NetworkX, How to do it…
- solve_congruence() function / How it works...
- SOPform() function
- about / How it works...
- sounds
- about / Sounds
- sound synthesizer
- creating, in notebook / Creating a sound synthesizer in the notebook, How it works...
- SourceForge
- about / Getting ready
- spam filtering / Supervised learning
- sparse decomposition
- about / Compressed sensing
- sparse matrices
- about / There's more...
- references / There's more...
- sparse matrix
- about /
- spatial locality / Why are NumPy arrays efficient?
- Spatial Poisson process
- reference / There's more...
- speech sounds
- digital filters, applying to / How to do it…, How it works...
- Sphinx
- URL / How to do it…
- about / How to do it…
- Split Bregman algorithm
- reference link / There's more...
- Split Bregman method
- about / How it works...
- Spyder
- SSE / Why are NumPy arrays efficient?
- Stack Overflow
- URL / How to do it…, How to do it…
- standalone Python programs
- memory_profiler package, using for / Using memory_profiler for standalone Python programs
- stash
- about / Stashing
- stashing
- about / Stashing
- state diagram / How it works...
- statistical average
- about / Frequentist and Bayesian methods
- statistical data analysis
- statistical hypothesis testing
- about / Getting started with statistical hypothesis testing – a simple z-test
- references / There's more...
- statistical inference
- statistical plots
- creating, with seaborn / Creating beautiful statistical plots with seaborn, How to do it…
- statistical textbooks
- reference / Parametric and nonparametric inference methods
- statistics
- reference / Parametric and nonparametric inference methods
- statsmodels
- URL / Getting ready
- about / How to do it...
- stats module
- stochastic algorithm
- stochastic cellular automata
- about / Introduction
- stochastic differential equation
- simulating / How to do it..., How it works...
- stochastic differential equations
- reference / There's more...
- Stochastic Differential Equations (SDEs)
- stochastic dynamical systems
- about / Introduction
- reference / References
- Stochastic Partial Differential Equations (SPDEs)
- about / Introduction
- stream processors
- about / How it works…
- strided indexing scheme / How it works...
- strides
- about / Using stride tricks with NumPy
- stride tricks
- using, with NumPy / Using stride tricks with NumPy, How to do it..., How it works...
- rolling average algorithm, implementing with / Implementing an efficient rolling average algorithm with stride tricks, How to do it...
- structure tensor / How it works...
- reference link / There's more...
- structuring element / How it works...
- subplots() function / How to do it…
- Sum of Products
- reference link / There's more...
- supervised learning
- about / Learning from data, Supervised learning
- reference link / Supervised learning
- Support Vector Classifier (SVC)
- about / How to do it...
- support vector machines (SVMs)
- about / Using support vector machines for classification tasks
- used, for classifying tasks / How to do it..., How it works...
- references / There's more…
- SVD decomposition
- reference link / There's more…
- SVG (Scalable Vector Graphics)
- about / How to do it...
- SWIG
- about / Introduction
- symbolic computing, SymPy / How to do it..., How it works...
- SymPy
- about / Introduction, Getting ready
- used, for symbolic computing / How to do it..., How it works...
- references / There's more...
- number theory / A bit of number theory with SymPy, How to do it..., How it works...
- Synthesizer
- URL / There's more...
T
- %%timeit cell magic / How it works...
- %timeit command / How it works...
- 2to3 tool
- about / Supporting both Python 2 and Python 3
- using / Using 2to3
- URL / Using 2to3
- task interface
- URL, for documentation / There's more…
- tasks
- classifying, support vector machines (SVMs) used / How to do it..., How it works...
- term frequency-inverse document-frequency
- reference link /
- test-driven development
- about / Workflows with unit testing
- test coverage
- about / Test coverage
- test functions for optimization
- reference / How to do it…
- test set
- about / Supervised learning
- test statistics
- about / How to do it...
- Text-To-Speech (TTS) / How to do it…
- text data
- handling, with scikit-learn /
- text editor
- IPython, using with / IPython and text editor
- text feature extraction, scikit-learn
- reference link /
- tf-idf
- about /
- Theano
- about / How it works…
- URL / There's more…
- thread
- about / How it works…
- timbre
- about / How it works...
- URL / There's more...
- time
- evaluating, by statement in IPython / How it works...
- time-dependent signals
- about / Introduction
- timeit.timeit() function
- about / There's more...
- time profiling
- about / Introduction
- time series
- about / Introduction, How it works...
- autocorrelation, computing of / Computing the autocorrelation of a time series, How to do it..., How it works...
- reference / There's more...
- topological sort
- used for resolving dependencies, in directed acyclic graph / Resolving dependencies in a directed acyclic graph with a topological sort, How to do it…
- topological sorting
- about / Resolving dependencies in a directed acyclic graph with a topological sort, There's more…
- reference link / There's more…
- Tornado
- reference / Architecture of the IPython notebook
- TortoiseGit
- URL / Getting ready
- total time
- about / How it works...
- total variation / How it works...
- total variation denoising
- about / How it works...
- reference link / There's more...
- trace module
- tracing tools
- train a cascade
- reference link / There's more...
- training set
- about / Supervised learning
- trait attributes
- about / How it works...
- transformations
- transition matrix / How it works...
- Traveling Salesman Problem
- reference link / Problems in graph theory
- truth table
- Boolean propositional formula, finding from / Finding a Boolean propositional formula from a truth table, How to do it...
- turbulence
- about / Differential equations
- Turing complete
- about / How it works...
- Twitter API, rate limit
- URL / Getting ready
- Twitter Developers website
- URL / Getting ready
- Twitter Python package
- URL / Getting ready
- two-dimensional array
- about / How to do it...
- typed memory views
- about / How it works…
U
- unconstrained optimization
- underfitting
- undirected graph
- about / Graphs
- uniforms / How it works…
- unit testing
- references / There's more...
- unit tests
- writing, with nose / Writing unit tests with nose, How to do it..., How it works...
- univariate method
- unsupervised learning
- about / Learning from data, Unsupervised learning
- reference link / Unsupervised learning
- unsupervised learning, terms
- clustering / Unsupervised learning
- density estimation / Unsupervised learning
- dimension reduction / Unsupervised learning
- manifold learning / Unsupervised learning
- unsupervised learning methods
- unsupervised learning tutorial, scikit-learn
- reference link / There's more…
- update() method / How it works...
- urllib2 module
- about / How to do it...
- user profile
- about / How it works...
V
- Vandermonde matrix
- variable / Learning from data
- variables / Univariate and multivariate methods
- variables types
- attributes / How it works…
- uniforms / How it works…
- variance
- varyings
- uniforms / How it works…
- texture samplers / How it works…
- vector
- about / How it works...
- vectorized instructions / Why are NumPy arrays efficient?
- vectorizer
- about /
- reference link /
- vectors
- about / Learning from data
- vector space / Learning from data
- Vega
- about / There's more…
- URL / There's more…
- vertex shader
- about / How to do it…
- vertices
- about / Graphs
- views
- Vincent
- Viola-Jones object detection framework
- about / How to do it...
- reference link / There's more...
- violin plot
- about / How to do it…
- VirtualBox
- URL / Getting ready
- virtualenv
- about / How to do it…
- Vispy
- about / Getting started with Vispy for high-performance interactive data visualizations, How it works…
- for scientific visualization / Vispy for scientific visualization
- references / Vispy for scientific visualization
- Vispy, for high-performance interactive data visualizations / Getting started with Vispy for high-performance interactive data visualizations, How to do it…, How it works…, There's more…
- visuals
- VizQL
- about / There's more…
- URL / There's more…
- voice frequency
- reference link / There's more...
- Von Neumann stability analysis
- references / There's more...
- Voronoi diagram
- about / Computing the Voronoi diagram of a set of points
- computing, of set of points / Computing the Voronoi diagram of a set of points, How to do it…
- reference link / There's more…
W
- Wakari
- warps
- about / How it works…
- wavelet transform
- about / Inverse Fourier Transform
- weave module
- about / There's more…
- webcam images
- processing, from notebook / Processing webcam images in real time from the notebook, How to do it..., How it works...
- WebCL
- about / There's more…
- WebGL
- about / How it works…
- white box model
- about / How it works...
- white noise
- about / How it works...
- reference / There's more...
- widget
- references / There's more...
- widget architecture, IPython notebook 2.0+
- references / There's more...
- Wiener process
- reference / There's more...
- Windows
- about / Windows
- Python 32-bit / Python 32-bit
- Python 64-bit / Python 64-bit
- DLL Hell / DLL hell
- Windows installer, Chris Gohlke's
- URL, for downloading / Getting ready
- Winpdb
- about / GUI debuggers
- Wolfram's code
- about / How to do it...
- reference / There's more...
- workflow, Git branching / A typical workflow with Git branching, How to do it…, How it works…
- workflows
- references / There's more…
- workflows, unit testing / Workflows with unit testing
- wrapper kernels
- about / There's more...
- reference / There's more...
Z
- z-score
- about / How to do it...
- z-test
- Zachary's Karate Club graph / How to do it…
- ZeroMQ (ZMQ)