Machine Learning Using R: With Time Series and Industry-Based Use Cases in R, 2/e
暫譯: 使用 R 的機器學習：包含時間序列與產業應用案例，第二版

Karthik Ramasubramanian, Abhishek Singh

Machine Learning Using R: With Time Series and Industry-Based Use Cases in R, 2/e

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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 second edition shows you how to work with a machine-learning algorithm and use it to build a ML model from raw data. You will see how to use R programming with TensorFlow, thus avoiding the effort of learning Python if you are only comfortable with R.

As in the first edition, the authors have kept the fine balance of theory and application of machine learning through various real-world use-cases which gives you a comprehensive collection of topics in machine learning. New chapters in this edition cover time series models and deep learning.

What You'll Learn 

 

 

  • Understand machine learning algorithms using R
  • Master the process of building machine-learning models 
  • Cover the theoretical foundations of machine-learning algorithms
  • See industry focused real-world use cases
  • Tackle time series modeling in R
  • Apply deep learning using Keras and TensorFlow in R

 

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 in practice using R.

商品描述(中文翻譯)

檢視使用 R 建立可擴展機器學習模型的最新技術進展，並利用大數據。本書第二版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。您將學會如何使用 R 程式語言與 TensorFlow，從而避免學習 Python 的麻煩，若您僅對 R 感到熟悉。

與第一版相同，作者保持了理論與應用之間的良好平衡，通過各種真實世界的案例，為您提供了機器學習主題的全面集合。本版新增的章節涵蓋時間序列模型和深度學習。

**您將學到什麼**

- 使用 R 理解機器學習演算法
- 精通構建機器學習模型的過程
- 涵蓋機器學習演算法的理論基礎
- 了解以行業為重點的真實案例
- 在 R 中處理時間序列建模
- 使用 Keras 和 TensorFlow 在 R 中應用深度學習

**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使用 R 實踐中的機器學習方法/演算法細微差別的學術研究者。

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