Data Science and Machine Learning with R

Chapters

Chapter 1: Introduction to Data Sciences and Machine Learning Chapter 2: Machine Learning Algorithms 
Chapter 3: Machine Learning Algorithms - II 
Chapter 4: Introduction to R
Chapter 5: More on Data Structures 
Chapter 6: Decision Control and Looping Statements 
Chapter 7: Generating and Manipulating Data in R 
Chapter 8: Working with Data 
Chapter 9: Using dplyr () and tidyr () packages
Chapter 10: Plotting graphs in R 
Chapter 11: Social Media Mining 
Chapter 12: Implementing Machine Learning Algorithms 
Chapter 13: Implementing Machine Learning Algorithms - II Index Online Content Appendices Case Studies

Overview

The book has been designed keeping in mind the needs of the beginners of this subject area while having no prior knowledge in this field. It is aimed to be used as a textbook for undergraduate and postgraduate students. However, it can also be used by research scholars and professionals. The text introduces the concepts of R programming language in a lucid way and enables the reader to use these to perform data science and machine learning applications for solving real-world problems. Every chapter in this book contains multiple programming exercises and examples that enhance the understanding of the subject.


Key Features

• Discussion on key topics such as ggplot 2 package, sentiment analysis, web scrapping, etc.
• Easy explanation of concepts along with programming applications
• Wide variety of pedagogical elements such as Chapter Highlights, Review Exercises, MCQs, Programming Exercises, etc. 
• Teaching aids such as ‘Programming Tips’ to help students remember important concepts and identify some typical errors

• Data Science and Machine Learning with R