Mastering Machine Learning with R : advanced machine learning techniques for building smartapplications with R 3.5, Third edition [E-Book] / Cory Lesmeister.
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...
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Full text |
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Personal Name(s): | Lesmeister, Cory, author |
Edition: |
3rd edition |
Imprint: |
[Birmingham] :
Packt Publishing,
2019
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Physical Description: |
344 pages (online resource) |
Note: |
englisch |
ISBN: |
9781789613568 9781789618006 |
Subject (ZB): | |
Subject (LOC): | |
Classification: |
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245 | 1 | 0 | |a Mastering Machine Learning with R : |b advanced machine learning techniques for building smartapplications with R 3.5, Third edition |h [E-Book] / |c Cory Lesmeister. |
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505 | 0 | |a Mastering Machine Learning with R : advanced machine learning techniques for building smart applications with R 3.5, Third edition -- Contributors -- Table of Contents -- Preface -- Chapter 1: Preparing and Understanding Data -- Chapter 2: Linear Regression -- Chapter 3: Logistic Regression -- Chapter 4: Advanced Feature Selection in Linear Models -- Chapter 5: K-Nearest Neighbors and Support Vector Machines -- Chapter 6: Tree-Based Classification -- Chapter 7: Neural Networks and Deep Learning -- Chapter 8: Creating Ensembles and Multiclass Methods -- Chapter 9: Cluster Analysis -- Chapter 10: Principal Component Analysis -- Chapter 11: Association Analysis -- Chapter 12: Time Series and Causality -- Chapter 13: Text Mining -- Creating a Package -- Other Books You May Enjoy -- Index. | |
520 | 3 | |a 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. By the end of this book, you'll be equipped with the skills to deploy ML techniques in your own projects or at work. | |
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