Artificial Intelligence with Python Cookbook

About this book

Artificial intelligence plays an integral role in automating problem-solving: predicting and classifying data, and training agents to execute tasks. This book teaches you to solve complex problems with independent recipes ranging from the essentials to methods fresh out of research.

It starts with setting up your Python environment and the fundamentals of data exploration, then moves through heuristic search techniques and genetic algorithms. You'll apply probabilistic models, constraint optimization, and reinforcement learning. As you progress, you'll build deep learning models for text, images, video, and audio, and work through algorithmic bias, style transfer, music generation, and AI use cases in healthcare and insurance.

By the end you'll have the skills to write AI and machine learning algorithms, test them, and deploy them for production.

Highlights

• Get up and running with AI using hands-on problem-solving recipes
• Explore Python libraries and tools to build AI solutions for images, text, and sound
• Implement NLP, reinforcement learning, deep learning, GANs, and Monte-Carlo tree search

What you'll learn

• Implement data preprocessing steps and optimize model hyperparameters
• Explore representational learning with adversarial autoencoders
• Use active learning, recommenders, knowledge embedding, and SAT solvers
• Get to grips with probabilistic modeling using TensorFlow Probability
• Run object detection, text-to-speech, and text and music generation
• Apply swarm algorithms, multi-agent systems, and graph networks
• Go from proof of concept to production by deploying models as microservices
• Understand how to use modern AI in practice

Who this book is for

For Python developers, data scientists, machine learning engineers, and deep learning practitioners who want to build AI solutions with easy-to-follow recipes. Basic working knowledge of Python and machine learning concepts helps you work with the code effectively.