/Mastering-Machine-Learning-with-R-Third-Edition

Mastering Machine Learning with R, Third edition, by Packt

Primary LanguageRMIT LicenseMIT

Mastering Machine Learning with R - Third Edition

Mastering Machine Learning with R - Third Edition

This is the code repository for Mastering Machine Learning with R - Third Edition, published by Packt.

Advanced machine learning techniques for building smart applications with R 3.5

What is this book about?

Given the growing popularity of R-zero-cost statistical programming environment, there has never been a better time to start applying ML to your data. This book will teach you advanced techniques in ML with the latest code in R 3.5. You will delve into various complex features of supervised learning, unsupervised learning and reinforcement learning algorithms to design efficient and powerful ML models.

This book covers the following exciting features:

  • Prepare data for machine learning methods with ease
  • Learn to write production-ready code and package it for use
  • Produce simple and effective data visualizations for improved insights
  • Master advanced methods such as Boosted Trees and deep neural networks
  • Use natural language processing to extract insights for text
  • Implement tree-based classifiers including Random Forest and Boosted Tree

If you feel this book is for you, get your copy today!

https://www.packtpub.com/

Instructions and Navigations

All of the code is organized into folders. For example, Chapter02.

The code will look like the following:

html, body, #map {
 height: 100%; 
 margin: 0;
 padding: 0
}

Following is what you need for this book: This book is for data science professionals, machine learning engineers, or anyone who is looking for the ideal guide to help them implement advanced machine learning algorithms. The book will help you take your skills to the next level and advance further in this field. Working knowledge of machine learning with R is mandatory.

With the following software and hardware list you can run all code files present in the book (Chapter 1-13).

Software and Hardware List

Chapter Software required OS required
All RStudio Windows, Mac OS X, and Linux (Any)

We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.

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Get to Know the Author

Cory Lesmeister has over fourteen years of quantitative experience and is currently a senior data scientist for the Advanced Analytics team at Cummins, Inc. in Columbus, Indiana. Cory spent 16 years at Eli Lilly and Company in sales, market research, Lean Six Sigma, marketing analytics, and new product forecasting.

Other books by the author

Mastering Machine Learning with R

Mastering Machine Learning with R - Second Edition

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