Book Image

Python Machine Learning Cookbook - Second Edition

By : Giuseppe Ciaburro, Prateek Joshi
Book Image

Python Machine Learning Cookbook - Second Edition

By: Giuseppe Ciaburro, Prateek Joshi

Overview of this book

This eagerly anticipated second edition of the popular Python Machine Learning Cookbook will enable you to adopt a fresh approach to dealing with real-world machine learning and deep learning tasks. With the help of over 100 recipes, you will learn to build powerful machine learning applications using modern libraries from the Python ecosystem. The book will also guide you on how to implement various machine learning algorithms for classification, clustering, and recommendation engines, using a recipe-based approach. With emphasis on practical solutions, dedicated sections in the book will help you to apply supervised and unsupervised learning techniques to real-world problems. Toward the concluding chapters, you will get to grips with recipes that teach you advanced techniques including reinforcement learning, deep neural networks, and automated machine learning. By the end of this book, you will be equipped with the skills you need to apply machine learning techniques and leverage the full capabilities of the Python ecosystem through real-world examples.
Table of Contents (18 chapters)

Stemming text data

When we deal with a text document, we encounter different forms of words. Consider the word play. This word can appear in various forms, such as play, plays, player, playing, and so on. These are basically families of words with similar meanings. During text analysis, it's useful to extract the base forms of these words. This will help us to extract some statistics to analyze the overall text. The goal of stemming is to reduce these different forms into a common base form. This uses a heuristic process to cut off the ends of words in order to extract the base form.

Getting ready

In this recipe, we will use the nltk.stem package that offers a processing interface for removing morphological affixes from...