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)

Predicting the quality of wine

In this recipe, we will predict the quality of wine based on the chemical properties of wines grown. The code uses a wine dataset, which contains a DataFrame with 177 rows and 13 columns; the first column contains the class labels. This data is obtained from the chemical analyses of wines grown in the same region in Italy (Piemonte) but derived from three different cultivars—namely, the Nebbiolo, Barberas, and Grignolino grapes. The wine from the Nebbiolo grape is called Barolo.

Getting ready

The data consists of the amounts of several constituents found in each of the three types of wines, as well as some spectroscopic variables. The attributes are as follows:

  • Alcohol
  • Malic acid
  • ...