Introduction to Data Science Using R

The book contains information not established in traditional statistical, R Programming, or computer science textbooks. The book takes one through basic statistics concepts and basic programming skills and in my view this is the most important information you will need for a career in data science. The book shows how data science is distinct from related fields and the value it brings to organizations using big data.
This book has three components:
1. An overview of what data science is and how it relates to other disciplines
2. Technical applications of the machine learning algorithms to discover and predict
3. Practical R Programming to practice for practicing and aspiring data scientists using R Package.
What This Book Covers:
The books explains why Data science is important taking relevant examples from different domains and explains statistical concepts and machine learning concepts. Then using basic statistical and mathematical concepts an approach is taken to input basic command in R to gets hands on experience with using the R programming Package for practical understanding. Another important part is case studies. Some have a statistical/machine learning flair, some have more of a business/decision science or operations research flair, and some have more of a data engineering flair.
"The book serves as a good introductory frame work for data science. It covers the basic concepts related to data science in a simple and lucid manner that will help the reader absorb the concepts easily. The reader can also practice the examples using R. Presentation of basic R commands will help the reader to start experimenting with R. Overall the book presents a good introduction to data science and its applications."
Dr. D. V. Srinivas Kumar,
Assisstant Professor,
School of Management Studies,
University of Hyderabad.
Contents:
1. Data Science: Key Concepts 2. Spotting Signals: An Overview 3. Problem based Analysis 4. Bivariate Analysis 5. Visual Constructs 6. Business Story Telling using R 7. Exploratory Data Analysis Case Study 8. Machine Learning in Action 9. Regression 10. Dimensionality Reduction Technique
About the Author:
Before taking on the assignment to write this book, Prema Alla trainedprofessionals and undertook consultancy work, working closely withAR Solutions Inc, 3 Executive Drive, Suite 351 Somerset NJ 08873.I wish to thank Derick Jose, who guided and mentored me through the whole process of writing this book.

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