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)

Representing for similarity search

In this recipe, we want to find a way to decide whether two strings are similar given a representation of those two strings. We'll try to improve the way strings are represented in order to make more meaningful comparisons between strings. But first, we'll get a baseline using more traditional string comparison algorithms.

We'll do the following: given a dataset of paired string matches, we'll try out different functions for measuring string similarity, then a bag-of-characters representation, and finally a Siamese neural network (also called a twin neural network) dimensionality reduction of the string representation. We'll set up a twin network approach for learning a latent similarity space of strings based on character n-gram frequencies.

A Siamese neural network, also sometimes called twin neural network, is named as such using the analogy of conjoined twins. It is a way to train a projection or a metric space. Two models...