Machine Learning Using R
暫譯: 使用 R 的機器學習

Karthik Ramasubramanian, Abhishek Singh

Machine Learning Using R

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商品描述

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 flow
  • Apply theoretical aspects of machine learning
  • Review industry-based cae studies
  • Understand ML algorithms using R
  • Build machine learning models using Apache Hadoop and Spark
 
Who This Book is For
 
Data scientists, data science professionals and researchers in academia who want to understand the nuances of machine learning approaches/algorithms along with ways to see them in practice using R. 
 
The book will also benefit the readers who want to understand the technology behind implementing a scalable machine learning model using Apache Hadoop, Hive, Pig and Spark.
 

商品描述(中文翻譯)


探討使用 R 建立可擴展機器學習模型的最新技術進展，並結合大數據。本書將教您如何使用機器學習演算法，並從原始數據構建 ML 模型。

所有實用的示範將在 R 中進行，這是一種強大的編程語言和統計計算及圖形的軟體環境。本書將使用 R 中的各種套件和方法來解釋主題。對於本書中涵蓋的每一種機器學習演算法，將提供理論、案例研究和實踐的三維方法。在適當的情況下，數學將通過 R 中的可視化進行解釋。所有圖像都將作為代碼下載的一部分提供彩色和高解析度版本。

這種新的機器學習教學範式將為許多認為這個主題難以學習的人帶來根本性的認知變化。儘管理論有時看起來很困難，特別是當涉及大量數學時，但本書提供的從理論到以範例驅動的學習的無縫過渡，使得讀者能夠輕鬆地將各個部分連接起來。


 

您將學到什麼 

 



  • 使用模型構建過程流程

  • 應用機器學習的理論方面

  • 回顧基於行業的案例研究

  • 使用 R 理解 ML 演算法

  • 使用 Apache Hadoop 和 Spark 構建機器學習模型


 


本書適合誰閱讀

 

數據科學家、數據科學專業人士以及希望理解機器學習方法/演算法細微差別的學術研究者，並希望使用 R 看到它們的實踐方式。

 

本書也將使希望理解使用 Apache Hadoop、Hive、Pig 和 Spark 實現可擴展機器學習模型背後技術的讀者受益。

 

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