Artificial Intelligence with Python by Joshi, Prateek -- Read -- Imperial Library of Trantor

Index

Title Page Copyright

Credits About the Author About the Reviewer www.PacktPub.com Customer Feedback Preface

What this book covers What you need for this book Who this book is for Conventions Reader feedback Customer support

Downloading the example code Downloading the color images of this book Errata Piracy Questions

Introduction to Artificial Intelligence

What is Artificial Intelligence? Why do we need to study AI? Applications of AI Branches of AI Defining intelligence using Turing Test Making machines think like humans Building rational agents General Problem Solver

Solving a problem with GPS

Building an intelligent agent

Types of models

Installing Python 3

Installing on Ubuntu Installing on Mac OS X Installing on Windows

Installing packages Loading data Summary

Classification and Regression Using Supervised Learning

Supervised versus unsupervised learning What is classification? Preprocessing data

Binarization Mean removal Scaling Normalization

Label encoding Logistic Regression classifier Naïve Bayes classifier Confusion matrix Support Vector Machines Classifying income data using Support Vector Machines What is Regression? Building a single variable regressor Building a multivariable regressor Estimating housing prices using a Support Vector Regressor Summary

Predictive Analytics with Ensemble Learning

What is Ensemble Learning?

Building learning models with Ensemble Learning

What are Decision Trees?

Building a Decision Tree classifier

What are Random Forests and Extremely Random Forests?

Building Random Forest and Extremely Random Forest classifiers Estimating the confidence measure of the predictions

Dealing with class imbalance Finding optimal training parameters using grid search Computing relative feature importance Predicting traffic using Extremely Random Forest regressor Summary

Detecting Patterns with Unsupervised Learning

What is unsupervised learning? Clustering data with K-Means algorithm Estimating the number of clusters with Mean Shift algorithm Estimating the quality of clustering with silhouette scores What are Gaussian Mixture Models? Building a classifier based on Gaussian Mixture Models Finding subgroups in stock market using Affinity Propagation model Segmenting the market based on shopping patterns Summary

Building Recommender Systems

Creating a training pipeline Extracting the nearest neighbors Building a K-Nearest Neighbors classifier Computing similarity scores Finding similar users using collaborative filtering Building a movie recommendation system Summary

Logic Programming

What is logic programming? Understanding the building blocks of logic programming Solving problems using logic programming Installing Python packages Matching mathematical expressions Validating primes Parsing a family tree Analyzing geography Building a puzzle solver Summary

Heuristic Search Techniques

What is heuristic search?

Uninformed versus Informed search

Constraint Satisfaction Problems Local search techniques

Simulated Annealing

Constructing a string using greedy search Solving a problem with constraints Solving the region-coloring problem Building an 8-puzzle solver Building a maze solver Summary

Genetic Algorithms

Understanding evolutionary and genetic algorithms Fundamental concepts in genetic algorithms Generating a bit pattern with predefined parameters Visualizing the evolution Solving the symbol regression problem Building an intelligent robot controller Summary

Building Games With Artificial Intelligence

Using search algorithms in games Combinatorial search Minimax algorithm Alpha-Beta pruning Negamax algorithm Installing easyAI library Building a bot to play Last Coin Standing Building a bot to play Tic-Tac-Toe Building two bots to play Connect Four™ against each other Building two bots to play Hexapawn against each other Summary

Natural Language Processing

Introduction and installation of packages Tokenizing text data Converting words to their base forms using stemming Converting words to their base forms using lemmatization Dividing text data into chunks Extracting the frequency of terms using a Bag of Words model Building a category predictor Constructing a gender identifier Building a sentiment analyzer Topic modeling using Latent Dirichlet Allocation Summary

Probabilistic Reasoning for Sequential Data

Understanding sequential data Handling time-series data with Pandas Slicing time-series data Operating on time-series data Extracting statistics from time-series data Generating data using Hidden Markov Models Identifying alphabet sequences with Conditional Random Fields Stock market analysis Summary

Building A Speech Recognizer

Working with speech signals Visualizing audio signals Transforming audio signals to the frequency domain Generating audio signals Synthesizing tones to generate music Extracting speech features Recognizing spoken words Summary

Object Detection and Tracking

Installing OpenCV Frame differencing Tracking objects using colorspaces Object tracking using background subtraction Building an interactive object tracker using the CAMShift algorithm Optical flow based tracking Face detection and tracking

Using Haar cascades for object detection Using integral images for feature extraction

Eye detection and tracking Summary

Artificial Neural Networks

Introduction to artificial neural networks

Building a neural network Training a neural network

Building a Perceptron based classifier Constructing a single layer neural network Constructing a multilayer neural network Building a vector quantizer Analyzing sequential data using recurrent neural networks Visualizing characters in an Optical Character Recognition database Building an Optical Character Recognition engine Summary

Reinforcement Learning

Understanding the premise Reinforcement learning versus supervised learning Real world examples of reinforcement learning Building blocks of reinforcement learning Creating an environment Building a learning agent Summary

Deep Learning with Convolutional Neural Networks

What are Convolutional Neural Networks? Architecture of CNNs Types of layers in a CNN Building a perceptron-based linear regressor Building an image classifier using a single layer neural network Building an image classifier using a Convolutional Neural Network Summary

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