Book Image

Artificial Intelligence with Python Cookbook

By : Ben Auffarth
Book Image

Artificial Intelligence with Python Cookbook

By: Ben Auffarth

Overview of this book

Artificial intelligence (AI) plays an integral role in automating problem-solving. This involves predicting and classifying data and training agents to execute tasks successfully. This book will teach you how to solve complex problems with the help of independent and insightful recipes ranging from the essentials to advanced methods that have just come out of research. Artificial Intelligence with Python Cookbook starts by showing you how to set up your Python environment and taking you through the fundamentals of data exploration. Moving ahead, you’ll be able to implement heuristic search techniques and genetic algorithms. In addition to this, you'll apply probabilistic models, constraint optimization, and reinforcement learning. As you advance through the book, you'll build deep learning models for text, images, video, and audio, and then delve into algorithmic bias, style transfer, music generation, and AI use cases in the healthcare and insurance industries. Throughout the book, you’ll learn about a variety of tools for problem-solving and gain the knowledge needed to effectively approach complex problems. By the end of this book on AI, you will have the skills you need to write AI and machine learning algorithms, test them, and deploy them for production.

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Table of Contents (13 chapters)
Preface
Preface
Who this book is for
What this book covers
To get the most out of this book
Sections
Get in touch
1
Getting Started with Artificial Intelligence in Python
Getting Started with Artificial Intelligence in Python
Technical requirements
Setting up a Jupyter environment
Getting proficient in Python for AI
Classifying in scikit-learn, Keras, and PyTorch
Modeling with Keras
Free Chapter
2
Advanced Topics in Supervised Machine Learning
Advanced Topics in Supervised Machine Learning
Technical requirements
Transforming data in scikit-learn
Predicting house prices in PyTorch
Live decisioning customer values
Battling algorithmic bias
Forecasting CO2 time series
3
Patterns, Outliers, and Recommendations
Patterns, Outliers, and Recommendations
Clustering market segments
Discovering anomalies
Representing for similarity search
Recommending products
Spotting fraudster communities
4
Probabilistic Modeling
Probabilistic Modeling
Technical requirements
Predicting stock prices with confidence
Estimating customer lifetime value
Diagnosing a disease
Stopping credit defaults
5
Heuristic Search Techniques and Logical Inference
Heuristic Search Techniques and Logical Inference
Making decisions based on knowledge
Solving the n-queens problem
Finding the shortest bus route
Simulating the spread of a disease
Writing a chess engine with Monte Carlo tree search
6
Deep Reinforcement Learning
Deep Reinforcement Learning
Technical requirements
Optimizing a website
Controlling a cartpole
Playing blackjack
7
Advanced Image Applications
Advanced Image Applications
Technical requirements
Recognizing clothing items
Generating images
Encoding images and style
8
Working with Moving Images
Working with Moving Images
Technical requirements
Localizing objects
Faking videos
9
Deep Learning in Audio and Speech
Deep Learning in Audio and Speech
Technical requirements
Recognizing voice commands
Synthesizing speech from text
Generating melodies
10
Natural Language Processing
Natural Language Processing
Technical requirements
Classifying newsgroups
Chatting to users
Translating a text from English to German
Writing a popular novel
11
Artificial Intelligence in Production
Artificial Intelligence in Production
Technical requirements
Visualizing model results
Serving a model for live decisioning
Securing a model against attack
12
Other Books You May Enjoy
Other Books You May Enjoy
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Other Books You May Enjoy

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  • Delve into deep probabilistic modeling with a Bayesian network
  • Create your own artwork using adversarial neural networks
  • Understand a model’s key performance characteristics and bring solutions to production as APIs
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Artificial Intelligence with Python - Second Edition
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