Browse Library
Sign In Start Free Trial
Close icon Search icon
Account
Browse Library Sign In Start Free Trial

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Book Overview & Buying Artificial Intelligence with Python
  • Table Of Contents Toc
Artificial Intelligence with Python

Artificial Intelligence with Python

By : Prateek Joshi
3.6 (34)
Buy this Book
close
close
Artificial Intelligence with Python

Artificial Intelligence with Python

3.6 (34)
By: Prateek Joshi
Buy this Book

Overview of this book

Artificial Intelligence is becoming increasingly relevant in the modern world. By harnessing the power of algorithms, you can create apps which intelligently interact with the world around you, building intelligent recommender systems, automatic speech recognition systems and more. Starting with AI basics you'll move on to learn how to develop building blocks using data mining techniques. Discover how to make informed decisions about which algorithms to use, and how to apply them to real-world scenarios. This practical book covers a range of topics including predictive analytics and deep learning.
Table of Contents (17 chapters)
close
close
close
Preface
Icon
Preface
Icon
What this book covers
Icon
What you need for this book
Icon
Who this book is for
Icon
Conventions
Icon
Reader feedback
Icon
Customer support
Lock Free Chapter
1
1. Introduction to Artificial Intelligence
Icon
1. Introduction to Artificial Intelligence
Icon
What is Artificial Intelligence?
Icon
Why do we need to study AI?
Icon
Applications of AI
Icon
Branches of AI
Icon
Defining intelligence using Turing Test
Icon
Making machines think like humans
Icon
Building rational agents
Icon
General Problem Solver
Icon
Building an intelligent agent
Icon
Installing Python 3
Icon
Installing packages
Icon
Loading data
Icon
Summary
2
2. Classification and Regression Using Supervised Learning
Icon
2. Classification and Regression Using Supervised Learning
Icon
Supervised versus unsupervised learning
Icon
What is classification?
Icon
Preprocessing data
Icon
Label encoding
Icon
Logistic Regression classifier
Icon
Naïve Bayes classifier
Icon
Confusion matrix
Icon
Support Vector Machines
Icon
Classifying income data using Support Vector Machines
Icon
What is Regression?
Icon
Building a single variable regressor
Icon
Building a multivariable regressor
Icon
Estimating housing prices using a Support Vector Regressor
Icon
Summary
3
3. Predictive Analytics with Ensemble Learning
Icon
3. Predictive Analytics with Ensemble Learning
Icon
What is Ensemble Learning?
Icon
What are Decision Trees?
Icon
What are Random Forests and Extremely Random Forests?
Icon
Dealing with class imbalance
Icon
Finding optimal training parameters using grid search
Icon
Computing relative feature importance
Icon
Predicting traffic using Extremely Random Forest regressor
Icon
Summary
4
4. Detecting Patterns with Unsupervised Learning
Icon
4. Detecting Patterns with Unsupervised Learning
Icon
What is unsupervised learning?
Icon
Clustering data with K-Means algorithm
Icon
Estimating the number of clusters with Mean Shift algorithm
Icon
Estimating the quality of clustering with silhouette scores
Icon
What are Gaussian Mixture Models?
Icon
Building a classifier based on Gaussian Mixture Models
Icon
Finding subgroups in stock market using Affinity Propagation model
Icon
Segmenting the market based on shopping patterns
Icon
Summary
5
5. Building Recommender Systems
Icon
5. Building Recommender Systems
Icon
Creating a training pipeline
Icon
Extracting the nearest neighbors
Icon
Building a K-Nearest Neighbors classifier
Icon
Computing similarity scores
Icon
Finding similar users using collaborative filtering
Icon
Building a movie recommendation system
Icon
Summary
6
6. Logic Programming
Icon
6. Logic Programming
Icon
What is logic programming?
Icon
Understanding the building blocks of logic programming
Icon
Solving problems using logic programming
Icon
Installing Python packages
Icon
Matching mathematical expressions
Icon
Validating primes
Icon
Parsing a family tree
Icon
Analyzing geography
Icon
Building a puzzle solver
Icon
Summary
7
7. Heuristic Search Techniques
Icon
7. Heuristic Search Techniques
Icon
What is heuristic search?
Icon
Constraint Satisfaction Problems
Icon
Local search techniques
Icon
Constructing a string using greedy search
Icon
Solving a problem with constraints
Icon
Solving the region-coloring problem
Icon
Building an 8-puzzle solver
Icon
Building a maze solver
Icon
Summary
8
8. Genetic Algorithms
Icon
8. Genetic Algorithms
Icon
Understanding evolutionary and genetic algorithms
Icon
Fundamental concepts in genetic algorithms
Icon
Generating a bit pattern with predefined parameters
Icon
Visualizing the evolution
Icon
Solving the symbol regression problem
Icon
Building an intelligent robot controller
Icon
Summary
9
9. Building Games With Artificial Intelligence
Icon
9. Building Games With Artificial Intelligence
Icon
Using search algorithms in games
Icon
Combinatorial search
Icon
Minimax algorithm
Icon
Alpha-Beta pruning
Icon
Negamax algorithm
Icon
Installing easyAI library
Icon
Building a bot to play Last Coin Standing
Icon
Building a bot to play Tic-Tac-Toe
Icon
Building two bots to play Connect Four™ against each other
Icon
Building two bots to play Hexapawn against each other
Icon
Summary
10
10. Natural Language Processing
Icon
10. Natural Language Processing
Icon
Introduction and installation of packages
Icon
Tokenizing text data
Icon
Converting words to their base forms using stemming
Icon
Converting words to their base forms using lemmatization
Icon
Dividing text data into chunks
Icon
Extracting the frequency of terms using a Bag of Words model
Icon
Building a category predictor
Icon
Constructing a gender identifier
Icon
Building a sentiment analyzer
Icon
Topic modeling using Latent Dirichlet Allocation
Icon
Summary
11
11. Probabilistic Reasoning for Sequential Data
Icon
11. Probabilistic Reasoning for Sequential Data
Icon
Understanding sequential data
Icon
Handling time-series data with Pandas
Icon
Slicing time-series data
Icon
Operating on time-series data
Icon
Extracting statistics from time-series data
Icon
Generating data using Hidden Markov Models
Icon
Identifying alphabet sequences with Conditional Random Fields
Icon
Stock market analysis
Icon
Summary
12
12. Building A Speech Recognizer
Icon
12. Building A Speech Recognizer
Icon
Working with speech signals
Icon
Visualizing audio signals
Icon
Transforming audio signals to the frequency domain
Icon
Generating audio signals
Icon
Synthesizing tones to generate music
Icon
Extracting speech features
Icon
Recognizing spoken words
Icon
Summary
13
13. Object Detection and Tracking
Icon
13. Object Detection and Tracking
Icon
Installing OpenCV
Icon
Frame differencing
Icon
Tracking objects using colorspaces
Icon
Object tracking using background subtraction
Icon
Building an interactive object tracker using the CAMShift algorithm
Icon
Optical flow based tracking
Icon
Face detection and tracking
Icon
Eye detection and tracking
Icon
Summary
14
14. Artificial Neural Networks
chevron up
Icon
14. Artificial Neural Networks
Icon
Introduction to artificial neural networks
Icon
Building a Perceptron based classifier
Icon
Constructing a single layer neural network
Icon
Constructing a multilayer neural network
Icon
Building a vector quantizer
Icon
Analyzing sequential data using recurrent neural networks
Icon
Visualizing characters in an Optical Character Recognition database
Icon
Building an Optical Character Recognition engine
Icon
Summary
15
15. Reinforcement Learning
Icon
15. Reinforcement Learning
Icon
Understanding the premise
Icon
Reinforcement learning versus supervised learning
Icon
Real world examples of reinforcement learning
Icon
Building blocks of reinforcement learning
Icon
Creating an environment
Icon
Building a learning agent
Icon
Summary
16
16. Deep Learning with Convolutional Neural Networks
Icon
16. Deep Learning with Convolutional Neural Networks
Icon
What are Convolutional Neural Networks?
Icon
Architecture of CNNs
Icon
Types of layers in a CNN
Icon
Building a perceptron-based linear regressor
Icon
Building an image classifier using a single layer neural network
Icon
Building an image classifier using a Convolutional Neural Network
Icon
Summary

Analyzing sequential data using recurrent neural networks

We have been dealing with static data so far. Artificial neural networks are good at building models for sequential data too. In particular, recurrent neural networks are great at modeling sequential data. Perhaps time-series data is the most commonly occurring form of sequential data in our world. You can learn more about recurrent neural networks at http://www.wildml.com/2015/09/recurrent-neural-networks-tutorial-part-1-introduction-to-rnns. When we are working with time-series data, we cannot just use generic learning models. We need to characterize the temporal dependencies in our data so that we can build a robust model. Let's see how to build it.

Create a new python file and import the following packages:

import numpy as np 
import matplotlib.pyplot as plt 
import neurolab as nl

Define a function to generate the waveforms. Start by defining four sine waves:

def get_data(num_points): 
    # Create sine waveforms...
CONTINUE READING
83
Tech Concepts
36
Programming languages
73
Tech Tools
Icon Unlimited access to the largest independent learning library in tech of over 8,000 expert-authored tech books and videos.
Icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Icon 50+ new titles added per month and exclusive early access to books as they are being written.
Artificial Intelligence with Python
End of Section 14
Next Section
notes
bookmark Notes and Bookmarks search Search in title playlist Add to playlist download Download options
font-size Font size

Change the font size

margin-width Margin width

Change margin width

day-mode Day/Sepia/Night Modes

Change background colour

Close icon Search
Country selected
Close icon Your notes and bookmarks

Confirmation

Modal Close icon
claim successful
Order Page Read Now

Buy this book with your credits?

Modal Close icon
Are you sure you want to buy this book with one of your credits?
Close
YES, BUY

Submit Your Feedback

Modal Close icon
Modal Close icon
Modal Close icon