Packt+ | Advance your knowledge in tech

0

All Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

Python Machine Learning By Example

You're reading from Python Machine Learning By Example The easiest way to get into machine learning

Product type Paperback

Published in May 2017

Publisher Packt

ISBN-13 9781783553112

Length 254 pages

Edition 1st Edition

Languages

Python

Tools

Matplotlib

Concepts

Machine Learning

Authors (2):

Yuxi (Hayden) Liu

Ivan Idris

View More author details

Table of Contents (15) Chapters

Title Page

Credits

About the Author

About the Reviewer

www.PacktPub.com

Customer Feedback

Preface

1. Getting Started with Python and Machine Learning FREE CHAPTER

2. Exploring the 20 Newsgroups Dataset with Text Analysis Algorithms

3. Spam Email Detection with Naive Bayes

4. News Topic Classification with Support Vector Machine

5. Click-Through Prediction with Tree-Based Algorithms

6. Click-Through Prediction with Logistic Regression

7. Stock Price Prediction with Regression Algorithms

8. Best Practices

The newsgroups data

The first project in this book is about the 20 newsgroups dataset found in scikit-learn. The data contains approximately 20,000 across 20 online newsgroups. A newsgroup is a place on the Internet where you can ask and answer questions about a certain topic. The data is already split into training and test sets. The cutoff point is at a certain date. The original data comes from http://qwone.com/~jason/20Newsgroups/. 20 different newsgroups are listed as follows:

comp.graphics
comp.os.ms-windows.misc
comp.sys.ibm.pc.hardware
comp.sys.mac.hardware
comp.windows.x
rec.autos
rec.motorcycles
rec.sport.baseball
rec.sport.hockey
sci.crypt
sci.electronics
sci.med
sci.space
misc.forsale
talk.politics.misc
talk.politics.guns
talk.politics.mideast
talk.religion.misc
alt.atheism
soc.religion.christian

All the documents in the dataset are in English. And from the newsgroup names, you can deduce the topics.

Some of the newsgroups are closely related or even overlapping, for instance, those five computer...

The rest of the chapter is locked

Register for a free Packt account to unlock a world of extra content!

A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.

Unlock this book and the full library FREE for 7 days

Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of

Start free trial

Renews at ₹800/month. Cancel anytime

Authors (2)

Yuxi (Hayden) Liu

Yuxi (Hayden) Liu

Yuxi (Hayden) Liu was a Machine Learning Software Engineer at Google. With a wealth of experience from his tenure as a machine learning scientist, he has applied his expertise across data-driven domains and applied his ML expertise in computational advertising, cybersecurity, and information retrieval. He is the author of a series of influential machine learning books and an education enthusiast. His debut book, also the first edition of Python Machine Learning by Example, ranked the #1 bestseller in Amazon and has been translated into many different languages.

See other products by Yuxi (Hayden) Liu

Ivan Idris

Ivan Idris

Ivan Idris has an MSc in experimental physics. His graduation thesis had a strong emphasis on applied computer science. After graduating, he worked for several companies as a Java developer, data warehouse developer, and QA analyst. His main professional interests are business intelligence, big data, and cloud computing. Ivan Idris enjoys writing clean, testable code and interesting technical articles. Ivan Idris is the author of NumPy 1.5. Beginner's Guide and NumPy Cookbook by Packt Publishing.

See other products by Ivan Idris

Other recommended products

Related to this chapter

Python Machine Learning By Example

Python Machine Learning By Example

Python Machine Learning by Example covers in detail the most important concepts, techniques, algorithms, and libraries that every data scientist or machine learning practitioner needs to know. This example-enriched guide will make your learning journey easier and happier, enabling you to solve real-world data-driven problems.

Feb 2019 12h 44m

Python Machine Learning By Example

Python Machine Learning By Example

Equipped with the latest updates, this third edition of Python Machine Learning By Example provides a comprehensive course for ML enthusiasts to strengthen their command of ML concepts, techniques, and algorithms.

Oct 2020 17h 32m

Machine Learning with scikit-learn Quick Start Guide

Machine Learning with scikit-learn Quick Start Guide

Scikit-learn is a robust machine learning library for the Python programming language. It provides a set of supervised and unsupervised learning algorithms. This book is the easiest way to learn how to deploy, optimize and evaluate all the important machine learning algorithms that scikit-learn provides.

Oct 2018 5h 44m

Mastering Machine Learning with scikit-learn

Mastering Machine Learning with scikit-learn

This book examines machine learning models including k-nearest neighbors, logistic regression, naive Bayes, random forests, and support vector machines. You will work through document classification, image recognition, and other example problems.

Jul 2017 8h 28m

scikit-learn Cookbook

scikit-learn Cookbook

scikit-learn has evolved as a robust library for machine learning applications in python with support for a wide range of supervised and unsupervised learning algorithms. This edition brings to you the various enhancements to its model implementations, API and bug fixes in the latest major release of scikit-learn to support Python. This book covers easy to follow recipes right from mathematical operations to implementing various supervised, unsupervised and deep learning algorithms with scikit-learn. Get practical hands-on knowledge to implement various models and algorithms like Multi-Layer Perceptrons, time-series split, MAE criterion for regression, criteria for gradient boosting, Classifier, Regressor, and much more.

Nov 2017 12h 28m

Ensemble Machine Learning Cookbook

Ensemble Machine Learning Cookbook

This book uses a recipe-based approach to showcase the power of machine learning algorithms to build ensemble models using Python libraries. Through this book, you will be able to pick up the code, understand in depth how it works, execute and implement it efficiently. This will be a desk reference to implement a wide range of tasks and solve the common and uncommon problems in ensemble machine learning domain.

Jan 2019 11h 12m

Hands-On Ensemble Learning with Python

Hands-On Ensemble Learning with Python

Ensemble learning can provide the necessary methods to improve the accuracy and performance of existing models. In this book, you'll understand how to combine different machine learning algorithms to produce more accurate results from your models.

Jul 2019 9h 56m

Machine Learning with Scala Quick Start Guide

Machine Learning with Scala Quick Start Guide

Scala as a programming language is a highly scalable integration of object-oriented and functional programming, which makes it easy to build scalable and complex big data applications. This book is a handy guide for machine learning developers and data scientists who want to train effective machine learning models using this popular language.

Apr 2019 7h 20m

Hands-On Machine Learning with scikit-learn and Scientific Python Toolkits

Hands-On Machine Learning with scikit-learn and Scientific Python Toolkits

This book covers the theory and practice of building data-driven solutions. Includes the end-to-end process, using supervised and unsupervised algorithms. With each algorithm, you will learn the data acquisition and data engineering methods, the apt metrics, and the available hyper-parameters. You will learn how to deploy the models in production.

Jul 2020 12h 48m

Python Machine Learning

Python Machine Learning

This second edition of Python Machine Learning by Sebastian Raschka is for developers and data scientists looking for a practical approach to machine learning and deep learning. In this updated edition, you'll explore the machine learning process using Python and the latest open source technologies, including scikit-learn and TensorFlow 1.x.

Sep 2017 20h 44m

Machine Learning Algorithms

Machine Learning Algorithms

Machine learning explores the study and construction of algorithms that can learn from, and make predictions on, data. This book will act as an entry point for anyone who wants to make a career in the field of Machine Learning. A few famous algorithms that are covered in this book are Linear regression, Logistic Regression, SVM, Naïve Bayes, K-Means, Random Forest, TensorFlow, and Feature engineering.

Jul 2017 12h 0m

Training Systems using Python Statistical Modeling

Training Systems using Python Statistical Modeling

This book will acquaint you with various aspects of statistical analysis in Python. You will work with different types of prediction models, such as decision trees, random forests and neural networks. By the end of this book, you will be confident in using various Python packages to train your own models for effective machine learning.

May 2019 9h 40m

Personalised recommendations for you

Based on your interests and search pattern

Mathematics of Machine Learning

Mathematics of Machine Learning

Deepen your theoretical knowledge and enhance your ability to solve complex machine learning problems with structured guidance. Gain the confidence to engage with advanced ML literature and tailor algorithms to meet your project requirements.

May 2025 24h 20m

Generative AI with Python and PyTorch

Generative AI with Python and PyTorch

Learn how to create images and text using VAEs, GANs, LSTMs, and transformers. Implement applications in natural language processing and computer vision through practical tutorials.

Mar 2025 15h 0m

Practical Generative AI with ChatGPT

Practical Generative AI with ChatGPT

This book helps you unlock ChatGPT's potential to make your working life better. From prompt engineering to creating custom GPTs, you'll enhance your productivity, creativity, and efficiency with practical insights and advanced techniques.

Apr 2025 12h 52m

Generative AI with LangChain

Generative AI with LangChain

Gain a solid foundation in LangChain, agentic AI, and LangGraph, and learn to build production-ready systems with multi-agent architectures, advanced RAG pipelines, Tree of Thought reasoning, agent handoffs, and fine-grained error handling.

May 2025 15h 52m

Architecting Power BI Solutions in Microsoft Fabric

Architecting Power BI Solutions in Microsoft Fabric

Power BI provides several options to solve common data problems, and designing the correct solution for each scenario can be a daunting task. This book makes it easier by guiding you through designing optimal solutions using Power BI.

Apr 2025 14h 16m

Microsoft Identity and Access Administrator SC-300 Exam Guide

Microsoft Identity and Access Administrator SC-300 Exam Guide

This comprehensive guide covers key topics such as Microsoft Entra ID implementation, authentication and access management, external user management, and hybrid identity solutions, providing practical insights and techniques for SC-300 exam success.

Mar 2025 19h 48m

LLM Design Patterns

LLM Design Patterns

This book helps you gain practical skills to develop and deploy LLMs. You'll learn data prep, training, pruning, quantization, and evaluation, as well as explore RAG, advanced prompting, and optimization to build robust, scalable language models.

May 2025 17h 48m

Tableau Cookbook for Experienced Professionals

Tableau Cookbook for Experienced Professionals

Advance your Tableau knowledge beyond the basics, streamline dashboard performance, tackle advanced geospatial challenges, and unlock API potential while fortifying your corporate data infrastructure with proven best practices.

Apr 2025 12h 24m

Time Series Analysis with Spark

Time Series Analysis with Spark

This book offers a complete guide to time series analysis with Apache Spark and Databricks, covering essential concepts and advanced techniques including Generative AI to equip readers with skills for real-world challenges across industries.

Mar 2025 9h 56m

Hands-On Artificial Intelligence for IoT

Hands-On Artificial Intelligence for IoT

Transform IoT systems with the power of artificial intelligence using this hands-on guide. Dive into practical techniques and expert insights to innovate and optimize your IoT devices, making them smarter and more efficient.

May 2025 15h 44m