Prema Alla eBooks
eBooks di Prema Alla
Introduction to Data Science Using Rsecond edition. E-book. Formato EPUB Prema Alla - Bsp Books, 2025 -
Dive into the world of data science with "Introduction to Data Science Using R, 2nd Edition." This comprehensive guide transcends conventional statistical and computer science textbooks by offering a fresh perspective on the essential skills needed for a successful career in data science.From demystifying basic statistics concepts to equipping you with fundamental programming abilities in R, this book is your gateway to understanding the distinctiveness and value of data science in contemporary organizations grappling with big data. Delve into the three core components of the book: an enlightening overview of data science's interdisciplinary nature, practical applications of machine learning algorithms for predictive insights, and hands-on R programming exercises tailored for aspiring data scientists.Unraveling the importance of data science through diverse real-world examples spanning various domains, this book seamlessly integrates statistical and machine learning theories with practical R programming commands. Embark on a journey of discovery with engaging case studies that blend statistical insights with business acumen, decision science, and data engineering prowess.Get ready to embark on a thrilling data science odyssey filled with knowledge, practical applications, and illuminating case studies in "Introduction to Data Science Using R, 2nd Edition."Contents:1.Data Science: Key Concepts2.Data Wrangling3.Spotting Signals: An Overview4.1. Introduction to R4.2. Business Storytelling Using R5.1. Problem based Analysis5.2. Model6.1. Bivariate Analysis6.2. Cross Tabs7. Correlation Matrix8.1. Visualization and Visual Constructs8.2. Advance Visualization9.1. Machine Learning in Action9.2. Decision Trees9.3. Support Vector Machines9.4. Naive Bayes9.5. Linear Regression9.6. Regression9.7. A/B Testing9.8. Classification9.9. Introduction to Gradient Boosting10.1. Sample Preparation10.2. Data Train and Test Data11.1. Multivariate Analysis Topics11.2. Principal Component Analysis11.3. Factor Analysis11.4. ANOVA12.1. Additional Topics in Analytics12.2. Exploratory Data Analysis Case Study – Business Perspective13. Text Mining
Introduction to Data Science Using R. E-book. Formato EPUB Prema Alla - Bsp Books, 2018 -
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.