| 書目名稱 | Machine Learning Using R |
| 編輯 | Karthik Ramasubramanian,Abhishek Singh |
| 視頻video | http://file.papertrans.cn/621/620429/620429.mp4 |
| 概述 | A comprehensive guide for anybody who wants to understand ML model building process end to end.Also covers scalable machine learning.Practical demonstration of concepts in R |
| 圖書封面 |  |
| 描述 | .Examine the latest technological advancements in building a scalable machine learning model with Big Data using R. This book shows you how to work with a machine learning algorithm and use it to build a ML model from raw data...All practical demonstrations will be explored in R, a powerful programming language and software environment for statistical computing and graphics. The various packages and methods available in R will be used to explain the topics. For every machine learning algorithm covered in this book, a 3-D approach of theory, case-study and practice will be given. And where appropriate, the mathematics will be explained through visualization in R. All the images are available in color and hi-res as part of the code download...This new paradigm of teaching machine learning will bring about a radical change in perception for many of those who think this subject is difficult to learn. Though theory sometimes looks difficult, especially when there is heavy mathematics involved, the seamless flow from the theoretical aspects to example-driven learning provided in?this book?makes it easy for someone to connect the dots...What You‘ll Learn?.Use the model building process fl |
| 出版日期 | Book 20171st edition |
| 關鍵詞 | Machine Learning; Data Exploration; Sampling Techniques; Data Visualization; Feature Engineering; Machine |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-1-4842-2334-5 |
| isbn_ebook | 978-1-4842-2334-5 |
| copyright | Karthik Ramasubramanian and Abhishek Singh 2017 |
|Archiver|手機版|小黑屋|
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