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Fundamentals of Data Science Using Python and R, (An Indian Adaptation) by Chantal D. Larose, Daniel T. Larose, Shaukat Ali Shahee

Fundamentals of Data Science Using Python and R, (An Indian Adaptation)

by Chantal D. Larose, Daniel T. Larose, Shaukat Ali Shahee
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Book cover type: Paperback
  • ISBN13: 9789363860759
  • Binding: Paperback
  • Subject: N/A
  • Publisher: Wiley
  • Publisher Imprint: Wiley
  • Publication Date:
  • Pages: 276
  • Original Price: INR 959.0
  • Language: English
  • Edition: N/A
  • Item Weight: 500 grams
  • BISAC Subject(s): N/A

Fundamentals of Data Science Using Python and R is an essential resource for students and professionals eager to explore data science with Python and R, two of the most popular open-source tools. The book covers the entire Data Science Methodology—from problem understanding to model deployment—and has been widely praised for its clarity and practicality. This adapted edition retains the core structure of the original, while enhancing end-of-chapter questions to suit the Indian academic environment. New examples and exercises focus on India-specific datasets, encouraging students to apply their knowledge to real-world scenarios relevant to India’s socio-economic and technological contexts. This hands-on approach ensures students gain both theoretical understanding and practical skills for a data-driven world. ·Introduction to Data Science ·The Basics of Python And R ·Data Preparation ·Explorator Y Data Analysis ·Preparing to Model The Data ·Decision Trees ·Model Evaluation ·Naïve Bayes Classification ·Neural Networks ·Clustering ·Regression Modeling ·Dimension Reduction ·Generalized Linear Models ·Association Rules

Chantal D. Larose Chantal D. Larose earned her PhD in Statistics from the University of Connecticut in 2015, focusing her dissertation on Model-Based Clustering of Incomplete Data. As an Assistant Professor of Decision Science at SUNY New Paltz, she played a pivotal role in developing the Bachelor of Science in Business Analytics program. Currently, she serves as an Assistant Professor of Statistics and Data Science at Eastern Connecticut State University, contributing to the design of the Mathematical Sciences Department’s data science curriculum. Daniel T. Larose Daniel T. Larose completed his PhD in Statistics from the University of Connecticut in 1996, with his dissertation titled Bayesian Approaches to Meta-Analysis. A Professor of Statistics and Data Science at Central Connecticut State University, he pioneered the world’s first online Master of Science in Data Mining in 2001. As the author or coauthor of 12 textbooks, Daniel also directs the online Master of Data Science program at CCSU and operates a consulting business. Shaukat Ali Shahee Shaukat Ali Shahee received his PhD from the SJM School of Management at the Indian Institute of Technology Bombay, where his research addressed challenges in analyzing imbalanced data with diverse intrinsic characteristics. His work has been featured in renowned journals such as International Journal of Artificial Intelligence and Soft Computing, Applied Intelligence, and Data Mining and Knowledge Discovery, as well as in the prestigious Advances in Data Mining book series. With 5.5 years of industry experience, he has served as a Quantitative Research Analyst at AlphaCrest Capital Management, a Deputy Manager at Bank of Maharashtra, and a Research Engineer at the IIT Bombay CSE department.

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