Mastering Machine Learning with R – Third Edition

Mastering Machine Learning with R, 3rd Edition

eBook Details:

  • Paperback: 354 pages
  • Publisher: WOW! eBook (January 31, 2019)
  • Language: English
  • ISBN-10: 1789618002
  • ISBN-13: 978-1789618006

eBook Description:

Mastering Machine Learning with R, 3rd Edition: Stay updated with expert techniques for solving data analytics and machine learning challenges and gain insights from complex projects and power up your applications

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 newly updated edition is packed with fresh examples covering a range of tasks from different domains. Mastering Machine Learning with R starts by showing you how to quickly manipulate data and prepare it for analysis. You will explore simple and complex models and understand how to compare them. You’ll also learn to use the latest library support such as TensorFlow and Keras-R for performing advanced computations. Additionally, you’ll explore complex topics such as natural language processing (NLP), time series analysis, and clustering, which will further refine your skills in developing applications. Each chapter will help you implement advanced ML algorithms using real-world examples. You’ll even be introduced to reinforcement learning along with its various use cases and models. Towards the concluding chapters, you’ll get a glimpse into how some of these black-box models can be diagnosed and understood.

  • 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

By the end of this Mastering Machine Learning with R, Third Edition book, you’ll be equipped with the skills to deploy ML techniques in your own projects or at work.

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