Data science and machine learning in R

By:

Thareja, Reema

Material type: Text

TextPublication details: McGraw Hill Education (India) Pvt. Ltd. Chennai 2021Description: xxiii, 472 pISBN:

9789354600333

Subject(s):

DDC classification:

006.31 THA

Summary: OVRERVIEW 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.

List(s) this item appears in: IT & Decision Sciences | Finance & Accounting

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Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Book	Indian Institute of Management LRC General Stacks	IT & Decisions Sciences	006.31 THA (Browse shelf(Opens below))	1	Available		002474

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Previous	006.31 SHA Deep learning with Tensorflow JS projects	006.31 SIL Beginning with deep learning using TensorFlow: a beginner’s guide to TensorFlow and Keras for practicing deep learning principles and applications	006.31 SRI Machine learning	006.31 THA Data science and machine learning in R	006.31 VER Industrial machine learning:	006.31 WIC Machine learning:	006.31015192 MUR Probabilistic machine learning: advanced topics	Next

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

OVRERVIEW

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.

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