0

Explore Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

Mastering Machine Learning with scikit-learn

You're reading from Mastering Machine Learning with scikit-learn Apply effective learning algorithms to real-world problems using scikit-learn

Product type Paperback

Published in Jul 2017

Publisher

ISBN-13 9781788299879

Length 254 pages

Edition 2nd Edition

Languages

Python

Tools

Scikit-learn

Concepts

Machine Learning

Author (1):

Gavin Hackeling

View More author details

Table of Contents (15) Chapters

Preface

1. The Fundamentals of Machine Learning FREE CHAPTER

2. Simple Linear Regression

3. Classification and Regression with k-Nearest Neighbors

4. Feature Extraction

5. From Simple Linear Regression to Multiple Linear Regression

6. From Linear Regression to Logistic Regression

7. Naive Bayes

8. Nonlinear Classification and Regression with Decision Trees

9. From Decision Trees to Random Forests and Other Ensemble Methods

10. The Perceptron

11. From the Perceptron to Support Vector Machines

12. From the Perceptron to Artificial Neural Networks

13. K-means

14. Dimensionality Reduction with Principal Component Analysis

What you need for this book

The examples in this book require Python >= 2.7 or >= 3.3 and pip, the PyPA recommended tool for installing Python packages. The examples are intended to be executed in a Jupyter notebook or an IPython interpreter. Chapter 1, The Fundamentals of Machine Learning shows how to install scikit-learn 0.18.1, its dependencies, and other libraries on Ubuntu, Mac OS, and Windows.

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 R$50/month. Cancel anytime

Authors (1)

Gavin Hackeling

Gavin Hackeling

Gavin Hackeling develops machine learning services for large-scale documents and image classification at an advertising network in New York. He received his Master's degree from New York University's Interactive Telecommunications Program, and his Bachelor's degree from the University of North Carolina.

See other products by Gavin Hackeling

Other recommended products

Related to this chapter

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

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

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

Python Data Mining Quick Start Guide

Python Data Mining Quick Start Guide

This book is an introduction to data mining and its practical demonstration of working with real-world data sets. With this book, you will be able to extract useful insights using common Python libraries. You will also learn key stages like data loading, cleaning, analysis, visualization to build an efficient data mining pipeline.

Apr 2019 6h 16m

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

Python Machine Learning

Python Machine Learning

This third edition is updated with TensorFlow 2 and the latest additions to scikit-learn. Packed with clear explanations, visualizations, and working examples, the book covers essential machine learning techniques in depth, along with two cutting-edge machine learning techniques: reinforcement learning and generative adversarial networks.

Dec 2019 25h 44m

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

Statistics for Machine Learning

Statistics for Machine Learning

This book will teach you all it takes to perform complex statistical computations required for Machine Learning. You will gain information on statistics behind supervised learning, unsupervised learning, reinforcement learning, and more. Understand the real-world examples that discuss the statistical side of Machine Learning and familiarize yourself with it.

Jul 2017 14h 44m

Supervised Machine Learning with Python

Supervised Machine Learning with Python

A supervised learning task infers a function from flagged training data and maps an input to an output based on sample input-output pairs. In this book, you will learn various machine learning techniques (such as linear and logistic regression) and gain the practical knowledge you need to quickly and powerfully apply algorithms to new problems.

May 2019 5h 24m

Hands-On Artificial Intelligence for Cybersecurity

Hands-On Artificial Intelligence for Cybersecurity

If you wish to design smart, threat-proof cybersecurity systems using trending AI tools and techniques, then this book is for you. With this book, you will learn to develop intelligent systems that can detect suspicious patterns and attacks, thereby allowing you to protect your network and corporate assets.

Aug 2019 11h 24m

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

Personalised recommendations for you

Based on your interests and search pattern

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Data Governance Handbook

Data Governance Handbook

This book provides a highly focused view of real business outcomes powered by data governance, that resonate with non-data executives such as CFOs and CEOs. You'll also find useful insights into how to implement data governance initiatives.

May 2024 13h 8m

Data Engineering with Databricks Cookbook

Data Engineering with Databricks Cookbook

This book shows you how to use Apache Spark, Delta Lake, and Databricks to build data pipelines, manage and transform data, optimize performance, and more. Additionally, you'll implement DataOps and DevOps practices, and orchestrate data workflows.

May 2024 14h 36m

Azure Data Engineer Associate Certification Guide

Azure Data Engineer Associate Certification Guide

Unlock the power of Azure data engineering with this certification guide, elevating your skills in data processing, storage, and security with the help of practical insights, hands-on exercises, and the latest advancements.

May 2024 18h 16m

Microsoft Power BI Cookbook

Microsoft Power BI Cookbook

Microsoft Power BI is the most sought-after platform for BI professionals' visualization needs. Explore the latest Power BI features, future AI enhancements, and integration with other Power Platform tools via new recipes in this updated edition.

Jul 2024 19h 56m

Python Data Cleaning Cookbook

Python Data Cleaning Cookbook

The book shows you how to clean, wrangle, and view data from multiple perspectives, including dataset and column attributes. You will cover common and not-so-common challenges that are faced while cleaning messy data for complex situations and learn to manipulate data to get it down to a form that can be useful for making the right decisions.

May 2024 16h 12m

Microsoft Azure AI Fundamentals AI-900 Exam Guide

Microsoft Azure AI Fundamentals AI-900 Exam Guide

This AI-900 study guide will help you prepare and practice for the certification exam. You'll delve into AI workloads, ML principles, computer vision, NLP, knowledge mining, and generative AI using Azure cloud services.

May 2024 9h 36m

Using Stable Diffusion with Python

Using Stable Diffusion with Python

This book shows you how to use Python to control Stable Diffusion and generate high-quality images. In addition to covering the basic usage of the diffusers package, the book provides solutions for extending the package for more advanced purposes.

Jun 2024 11h 44m

Getting Started with DuckDB

Getting Started with DuckDB

This hands-on book teaches you to analyze large datasets with blazing speed and ease. You will learn how to use DuckDB to quickly load, query, transform, analyze, and visualize data effectively through a series of practical examples.

Jun 2024 12h 44m

Databricks Certified Associate Developer for Apache Spark Using Python

Databricks Certified Associate Developer for Apache Spark Using Python

This guide gets you ready for certification with expert-backed content, key exam concepts, and topic reviews. Additionally, you'll be able to make the most of Apache Spark 3.0 to modernize workloads and more using specific tools and techniques.