Index
A
- activation function
- setting up, with sigmoid / Setting up the activation function with sigmoid, How it works...
- about / See also
- threshold function / See also
- sigmoid function / See also
- Hyperbolic Tangent function (tanh) / See also
- Rectified Linear Unit (ReLU) function / See also
- Maxout function / See also
- Adam Optimizer
- reference / See also
- Apple
- stock market data, downloading / Downloading stock market data for Apple, How to do it..., How it works..., There's more...
- stock market data, exploring / Exploring and visualizing stock market data for Apple, There's more...
- stock market data, visualizing / Exploring and visualizing stock market data for Apple, There's more...
- array
- PySpark dataframe, converting to / Converting a PySpark dataframe to an array, How it works...
- visualizing, in scatterplot / Visualizing an array in a scatterplot, How to do it..., How it works...
- validating, for optimal neural network performance / Validating array for optimal neural network performance
- artificial neural network
- reference / See also
B
- backpropagation
- references / See also
- bash / Getting ready
- BinaryClassificationEvaluator
- URL / See also
- bokeh
- URL / See also
C
- cell state / How to do it...
- classification and regression, PySpark
- reference link / See also
- classification models / Introduction
- Cloudera
- reference link / See also
- columns
- manipulating, in PySpark dataframe / Manipulating columns in a PySpark dataframe, How it works...
- convolutional neural networks (CNNs)
- about / Introduction
- high-level libraries, prioritizing / Pain Point #6: Prioritizing high-level libraries for CNNs, Getting ready, How it works..., There's more...
- cost function
- calculating, in neural network / Calculating the cost function in a neural network, How to do it...
D
- data
- cleansing / Preparing and cleansing data
- DataBricks
- reference link / See also
- data dictionary
- reference / There's more...
- dataframe
- creating, in PySpark / Creating a dataframe in PySpark, How to do it..., How it works...
- data normalization
- URL / See also
- using / There's more...
- dataset
- preparing, for deep learning pipeline / Preparing dataset for the deep learning pipeline, How it works...
- deep convolutional networks
- used, for face recognition / Introduction
- deep learning model
- about / Introduction
- applying, with Keras / Applying the deep learning model with Keras, How it works..., There's more...
- deep learning packages
- PySpark installation, configuring / Configuring PySpark installation with deep learning packages, How it works...
- deep learning pipeline
- dataset, preparing / Preparing dataset for the deep learning pipeline, How it works...
- derivatives
- reference / See also
- dropout / See also
E
- exploding gradient problem
- exploratory analysis
- data, visualization / Performing exploratory analysis and visualization, How to do it..., How it works..., There's more..., See also
F
- face recognition
- with deep convolutional networks / Introduction
- MIT-CBCL dataset, downloading into memory / Downloading and loading the MIT-CBCL dataset into the memory, How to do it..., How it works..., There's more...
- MIT-CBCL dataset, loading into memory / Downloading and loading the MIT-CBCL dataset into the memory, How to do it..., How it works..., There's more...
- images, plotting from directory / Plotting and visualizing images from the directory, How to do it..., How it works..., There's more...
- images, visualizing from directory / Plotting and visualizing images from the directory, How to do it..., How it works..., There's more...
- images, preprocessing / Preprocessing images, Getting ready, How to do it..., How it works..., There's more...
- model, building / Model building, training, and analysis, How to do it..., How it works..., There's more...
- model, training / Model building, training, and analysis, How to do it..., How it works..., There's more...
- model analysis / Model building, training, and analysis, How to do it..., How it works..., There's more...
- false negative (FN) / How it works...
- feature selection / Preparing feature variables for the logistic regression model
- feedforward networks
- about / Introduction to feedforward networks, How to do it..., There's more...
- working / How it works...
- fine-tuning model parameters / Fine-tuning model parameters, There's more...
- fire department call prediction
- dataset, downloading / Downloading the San Francisco fire department calls dataset, Getting ready, How to do it..., How it works..., There's more...
- target variable, identifying with logistic regression model / Identifying the target variable of the logistic regression model, How to do it..., How it works..., There's more...
- Firefox add-ons
- downloading link / How to do it...
- footballers
- images, downloading / Downloading 30 images each of Messi and Ronaldo, How to do it..., How it works...
- forget gate / How it works...
G
- Gated Recurrent Units (GRUs) / There's more..., Introduction
- gates / How to do it...
- gender prediction
- based on height/weight / Getting ready, How it works...
- Google Cloud Platform
- Ubuntu Desktop, installing / Installing and configuring Ubuntu Desktop for Google Cloud Platform, How to do it..., How it works...
- Ubuntu Desktop, configuring / Installing and configuring Ubuntu Desktop for Google Cloud Platform, How to do it..., How it works...
- URL / See also
- gradient descent
- reference / See also
H
- hidden layers / How to do it...
- Hortonworks
- reference link / See also
I
- image classification training
- pipeline, creating / Creating a pipeline for image classification training, There's more...
- IMDB
- reference link / How it works...
- Inception
- URL / See also
- input data
- normalizing, for neural network / Normalizing the input data for the neural network, How to do it..., How it works...
- input gate layer / How to do it...
- input text
- novels/books, downloading / Getting ready, How to do it..., How it works...
- interactive developing environment (IDE) / Integrating Jupyter notebooks with Spark
J
- Java virtual machine (JVM) / How it works...
- Jupyter notebooks
- integrating, with Spark / Integrating Jupyter notebooks with Spark, How it works..., There's more...
K
- Kaggle
- URL / Getting ready
- keras
- URL, for model tuning / See also
- deep learning model, applying / Applying the deep learning model with Keras, How it works..., There's more...
- keras layers
- references / See also
- King County House sales dataset
- downloading / Getting ready, How it works..., There's more...
- references / See also
- exploratory analysis, performing / Performing exploratory analysis and visualization, See also
- exploratory analysis, visualization / Performing exploratory analysis and visualization, See also
- price and features, correlation plotting / Plotting correlation between price and other features, How it works..., There's more...
- price, evaluation / Predicting the price of a house, How it works..., There's more..., See also
L
- Latin1 encoding formats
- URL / There's more...
- lexicon / How it works...
- linear regression model
- references / Getting ready
- logistic regression model
- feature variables, preparing / Preparing feature variables for the logistic regression model, How it works..., There's more...
- applying / Applying the logistic regression model, How to do it..., How it works..., There's more...
- accuracy, evaluating / Evaluating the accuracy of the logistic regression model, There's more...
- reference link / See also
- long-term dependencies / How to do it...
- Long Short-Term Memory Units (LSTMs) / Introduction
- about / There's more..., How to do it..., There's more..., Introduction, Training and saving the LSTM model, How it works...
- sequential working / Sequential working of LSTMs
- working / How it works...
- data, preparing / Preparing and cleansing data, How it works...
- data, cleansing / How it works...
- references, for data preparation / See also
- sentences, tokenizing / Tokenizing sentences
- training / Training and saving the LSTM model, How it works...
- saving / Training and saving the LSTM model, How it works...
- references / There's more...
- used, for generating similar text / Generating similar text using the model, How to do it..., How it works..., There's more...
- building / Building the LSTM model, How to do it..., How it works...
- evaluating / Evaluating the model, How it works...
M
- macOS
- Ubuntu, installing with VMWare Fusion / Getting ready, How to do it...
- Ubuntu, configuring with VMWare Fusion / Getting ready, How to do it...
- MapR
- reference link / See also
- matplotlib
- reference / See also
- model performance
- evaluating / Evaluating model performance, There's more...
- Modified National Institute of Standards and Technology (MNIST)
- images, importing / Pain Point #1: Importing MNIST images, How it works..., There's more..., See also
- images, visualizing / Pain Point #2: Visualizing MNIST images, How to do it..., How it works..., There's more...
- images, exporting as files / Pain Point #3: Exporting MNIST images as files, How it works..., See also
- images, augmenting / Pain Point #4: Augmenting MNIST images, How it works..., There's more...
- MovieLens datasets
- downloading / Downloading MovieLens datasets, How to do it..., How it works..., See also
- reference link / How to do it..., See also
- manipulating / Manipulating and merging the MovieLens datasets, How it works..., There's more...
- merging / Manipulating and merging the MovieLens datasets, How it works..., There's more...
- exploring / Exploring the MovieLens datasets, How it works..., There's more...
N
- natural language processing (NLP)
- about / Introduction
- therapy bot session text dataset, downloading / Downloading the therapy bot session text dataset, How to do it..., There's more...
- therapy bot session dataset, analyzing / Analyzing the therapy bot session dataset, How it works...
- stop words, removing from text / Removing stop words from the text, How it works..., See also
- Netflix Prize
- reference link / See also
- neural network
- biases, setting up for input / Setting up weights and biases for input into the neural network, Getting ready, How it works...
- weights, setting up for input / Setting up weights and biases for input into the neural network, Getting ready, How it works...
- input data, normalizing / Normalizing the input data for the neural network, How to do it..., How it works...
- cost function, calculating / Calculating the cost function in a neural network, How to do it...
- normalization
- reference / See also
- numpy.stack()
- reference / See also
O
- one hot encoding
- URL / See also
- references / Getting ready
- optimal neural network performance
- array, validating for / Validating array for optimal neural network performance
- Oracle VirtualBox
- used, for installing Ubuntu on Windows / Installing and configuring Ubuntu with Oracle VirtualBox on Windows, How it works...
- used, for configuring Ubuntu on Windows / Installing and configuring Ubuntu with Oracle VirtualBox on Windows, How it works...
- overfitting
- URL / See also
P
- Parametric Rectified Linear Unit (PReLU) / See also
- pipeline
- creating, or image classification training / Creating a pipeline for image classification training, There's more...
- plotly
- URL / See also
- prediction scores
- visualizing / Visualizing prediction scores, How to do it..., How it works...
- predictive model / Predicting gender based on height and weight
- prerequisites
- installing, on Ubuntu Desktop / Installing and configuring Spark and prerequisites on Ubuntu Desktop, How to do it..., How it works...
- configuring, on Ubuntu Desktop / Installing and configuring Spark and prerequisites on Ubuntu Desktop, How to do it..., How it works...
- price predictions / Predicting the price of a house, How it works..., There's more..., See also
- Project Gutenberg
- URL / Getting ready
- PySpark
- dataframe, creating / Creating a dataframe in PySpark, How to do it..., How it works...
- pyspark.sql module
- reference / See also
- PySpark dataframe
- columns, manipulating / Manipulating columns in a PySpark dataframe, How it works...
- converting, to array / Converting a PySpark dataframe to an array, How it works...
- images, loading / Loading images on to PySpark dataframes, How it works...
- PySpark installation
- configuring, with deep learning packages / Configuring PySpark installation with deep learning packages, How it works...
Q
- Quickstart
- for macOS, reference link / How to do it...
R
- recall / How it works...
- recommendation engine's accuracy
- evaluating / Evaluating the recommendation engine's accuracy
- rectified linear unit (relu) / How it works...
- recurrent neural network (RNN)
- about / There's more..., Introduction, How it works...
- sequential workings / Sequential workings of RNNs, How to do it..., How it works..., There's more...
- URL / Getting ready
- regular expressions
- URL / See also
- ResNet
- URL / See also
S
- scatterplot
- array, visualizing / Visualizing an array in a scatterplot, How to do it..., How it works...
- seaborn
- sentences, tokenizing / Tokenizing sentences, How it works...
- sentiment analysis
- calculating, of text / Calculating sentiment analysis of text, How it works...
- sigmoid
- activation function, setting up / Setting up the activation function with sigmoid, How it works...
- reference / See also
- sigmoid derivative function
- Software Development Kit (SDK) / How it works...
- Spark
- installing, on Ubuntu Desktop / Installing and configuring Spark and prerequisites on Ubuntu Desktop, How to do it..., How it works...
- configuring, on Ubuntu Desktop / Installing and configuring Spark and prerequisites on Ubuntu Desktop, How to do it..., How it works...
- used, for integrating Jupyter notebooks / Integrating Jupyter notebooks with Spark, How it works..., There's more...
- Spark cluster
- starting / Starting and configuring a Spark cluster, There's more...
- configuring / Starting and configuring a Spark cluster, There's more...
- stopping / Stopping a Spark cluster, There's more...
- sparkdl package
- reference link / See also
- Spark machine learning pipeline
- URL / See also
- SQL programming
- URL / See also
- stock market data
- downloading, for Apple / Downloading stock market data for Apple, How to do it..., How it works..., There's more...
- exploring, for Apple / Exploring and visualizing stock market data for Apple, There's more...
- visualizing, for Apple / Exploring and visualizing stock market data for Apple, There's more...
- preparing, for model performance / Preparing stock data for model performance, How to do it..., How it works..., There's more...
- stop words
- removing, from text / Removing stop words from the text, How it works...
- URL / See also
- StopWordsRemover
- URL / See also
T
- t-distributed Stochastic Neighbor Embedding (t-SNE)
- about / How it works...
- URL / See also
- Term Frequency-Inverse Document Frequency (TF-IDF)
- about / Introduction
- word counts, visualizing in dataset / Visualizing word counts in the dataset, See also
- sentiment analysis, calculating of text / Calculating sentiment analysis of text, How it works...
- training / Training the TF-IDF model, How it works..., There's more...
- URL / See also
- performance, evaluating / Evaluating TF-IDF model performance, How it works...
- performance, comparing to baseline score / Comparing model performance to a baseline score, How it works...
- TextBlob library
- URL / See also
- therapy bot session text dataset
- tokenizing
- references / There's more...
- trained images
- alternate sources, utilizing / Pain Point #5: Utilizing alternate sources for trained images, How to do it..., There's more...
- Transactions on Interactive Intelligent Systems (TiiS) / Getting ready
- transfer learning
- about / Understanding transfer learning, How it works...
- reference link / See also
U
- Ubuntu
- configuring, on macOS with VMWare Fusion / Installing and configuring Ubuntu with VMWare Fusion on macOS, How to do it...
- installing, on macOS with VMWare Fusion / Installing and configuring Ubuntu with VMWare Fusion on macOS, How to do it...
- installing, with Oracle VirtualBox on Windows / Installing and configuring Ubuntu with Oracle VirtualBox on Windows, How it works...
- configuring, with Oracle VirtualBox on Windows / Installing and configuring Ubuntu with Oracle VirtualBox on Windows, How it works...
- Ubuntu Desktop
- image, downloading / Downloading an Ubuntu Desktop image, How it works...
- downloading link / How to do it...
- installing, for Google Cloud Platform / Installing and configuring Ubuntu Desktop for Google Cloud Platform, How to do it..., How it works...
- configuring, for Google Cloud Platform / Installing and configuring Ubuntu Desktop for Google Cloud Platform, How to do it..., How it works...
- Spark, installing / Installing and configuring Spark and prerequisites on Ubuntu Desktop, How to do it..., How it works...
- Spark, configuring / Installing and configuring Spark and prerequisites on Ubuntu Desktop, How to do it..., How it works...
- prerequisites, installing / Installing and configuring Spark and prerequisites on Ubuntu Desktop, How to do it..., How it works...
- prerequisites, configuring / Installing and configuring Spark and prerequisites on Ubuntu Desktop, How to do it..., How it works...
- update gate / How it works...
- UTF-8
- URL / There's more...
V
- vanishing gradient problem
- variables, encoding
- URL / See also
- VectorAssembler
- URL / See also
- VMWare Fusion
- used, for installing Ubuntu on macOS / Installing and configuring Ubuntu with VMWare Fusion on macOS, How to do it...
- used, for configuring Ubuntu on macOS / Installing and configuring Ubuntu with VMWare Fusion on macOS, How to do it...
- VMware Fusion 10
- downloading link / Getting ready
- VNC Viewer
- downloading link / How to do it...
W
- Windows
- Ubuntu, installing with Oracle VirtualBox / Installing and configuring Ubuntu with Oracle VirtualBox on Windows, How it works...
- Ubuntu, configuring with Oracle VirtualBox / Installing and configuring Ubuntu with Oracle VirtualBox on Windows, How it works...
- word counts
- visualizing, in dataset / Visualizing word counts in the dataset, See also
- Word Vectors
- creating, with Word2Vec / Introduction
- data, acquiring / Acquiring data, How it works...
- libraries, importing / Importing the necessary libraries, How to do it..., How it works..., There's more...
- references / See also
- data, preparing / Preparing the data, How to do it..., How it works...
- model, building / Building and training the model, How it works..., There's more...
- model, training / Building and training the model, How it works..., There's more...
- visualizing / Visualizing further , How it works...
- analyzing / Analyzing further, How it works...