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.
Table of Contents (13 chapters)
Natural Language Processing

Natural language processing (NLP) is about analyzing texts and designing algorithms to process texts, making predictions from texts, or generating more text. NLP covers anything related to language, often including speech similar to what we saw in the Recognizing voice commands recipe in Chapter 9, Deep Learning in Audio and Speech. You might also want to refer to the Battling algorithmic bias recipe in Chapter 2, Advanced Topics in Supervised Machine Learning, or the Representing for similarity search recipe in Chapter 3, Patterns, Outliers, and Recommendations, for more traditional approaches. Most of this chapter will deal with the deep learning models behind the breakthroughs in recent years.

Language is often seen to be intrinsically linked to human intelligence, and machines mastering communication capabilities have long been seen as closely intertwined...