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)
Working with Moving Images

This chapter deals with video applications. While methods applied to images can be applied to single frames of videos, this usually comes with a loss of temporal consistency. We will try to strike a balance between what's possible on consumer hardware and what's interesting enough to show and implement.

Quite a few applications should come to mind when talking about video, such as object tracking, event detection (surveillance), deep fake, 3D scene reconstruction, and navigation (self-driving cars).

A lot of them require many hours or days of computation. We'll try to strike a sensible compromise between what's possible and what's interesting. This compromise might be felt more than in other chapters, where computations are not as demanding as for video. As part of this compromise, we'll work on videos frame by frame, rather...