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.
Implement data preprocessing steps and optimize model hyperparameters
Delve into representational learning with adversarial autoencoders
Use active learning, recommenders, knowledge embedding, and SAT solvers
Get to grips with probabilistic modeling with TensorFlow probability
Run object detection, text-to-speech conversion, 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