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)
Deep Learning in Audio and Speech

In this chapter, we'll deal with sounds and speech. Sound data comes in the form of waves, and therefore requires different preprocessing than other types of data.

Machine learning on audio signals finds commercial applications in speech enhancement (for example, in hearing aids), speech-to-text and text-to-speech, noise cancellation (as in headphones), recommending music to users based on their preferences (such as Spotify), and generating audio. Many fun problems can be encountered in audio, including the classification of music genres, the transcription of music, generating music, and many more besides.

We'll implement several applications with sound and speech in this chapter. We'll first do a simple example of a classification task, where we try to distinguish different words. This would be a typical application in a smart...