Machine Learning Using R: With Time Series and Industry-Based Use Cases in R
Authors: Karthik Ramasubramanian – Abhishek Singh
ISBN-10: 1484242149
ISBN-13: 9781484242148
Edition 版次: 2nd ed.
Publication Date 出版日期: 2018-12-13
Print Length 页数: 700 pages
Book Description
By finelybook
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
Cover
1.Introduction to Machine Learning andR
2.Data Preparation and Exploration
3.Sampling and Resampling Techniques
4.Data Visualization in R
5.Feature Engineering
6.Machine Learning Theory and Practice
7.Machine Learning Model Evaluation
8.Model Performance Improvement
9.Time Series Modeling
10.Scalable Machine Learning and Related Technologies
11.Deep Learning Using Keras and TensorFlow
