Foundations Of Data Science With Python
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Foundations of Data Science with Python
Foundations of Data Science with Python introduces readers to the fundamentals of data science, including data manipulation and visualization, probability, statistics, and dimensionality reduction. This book is targeted toward engineers and scientists, but it should be readily understandable to anyone who knows basic calculus and the essentials of computer programming. It uses a computational-first approach to data science: the reader will learn how to use Python and the associated data-science libraries to visualize, transform, and model data, as well as how to conduct statistical tests using real data sets. Rather than relying on obscure formulas that only apply to very specific statistical tests, this book teaches readers how to perform statistical tests via resampling; this is a simple and general approach to conducting statistical tests using simulations that draw samples from the data being analyzed. The statistical techniques and tools are explained and demonstrated using a diverse collection of data sets to conduct statistical tests related to contemporary topics, from the effects of socioeconomic factors on the spread of the COVID-19 virus to the impact of state laws on firearms mortality. This book can be used as an undergraduate textbook for an Introduction to Data Science course or to provide a more contemporary approach in courses like Engineering Statistics. However, it is also intended to be accessible to practicing engineers and scientists who need to gain foundational knowledge of data science. Key Features: Applies a modern, computational approach to working with data Uses real data sets to conduct statistical tests that address a diverse set of contemporary issues Teaches the fundamentals of some of the most important tools in the Python data-science stack Provides a basic, but rigorous, introduction to Probability and its application to Statistics Offers an accompanying website that provides a unique set of online, interactive tools to help the reader learn the material
Foundations of Data Science
Author: Dr. Talluri Sunil Kumar, Dr. Radhika Pathi, Mr. Venu Aluri, K. Balasubramanian
language: en
Publisher: RK Publication
Release Date: 2025-05-02
Foundations of Data Science offers a comprehensive introduction to data analysis, statistical modeling, machine learning, and computational techniques. Designed for students and professionals, it blends theory with practical applications, emphasizing critical thinking and data-driven decision-making across disciplines. The book equips readers to solve real-world problems using modern data science tools.
Foundations of Data Science- Principles and Applications
Author: Dr. Punit Kumar Chaubey
language: en
Publisher: Academic Guru Publishing House
Release Date: 2024-07-24
The thorough reference "Foundations of Data Science: Principles and Applications" explores the fundamental ideas and real-world uses of data science. The book is appropriate for both novices and those wishing to expand their knowledge of the subject since it is organised to lead readers from the fundamentals to more complex subjects. The book is broken up into many important parts. The first few chapters cover foundational ideas such data types, statistical procedures, and data visualisation strategies. Big data analytics, data mining methods, and machine learning algorithms are introduced throughout the book. A combination of practical examples and theoretical insights are used to convey each subject, making sure that readers not only understand the ideas but also learn how to apply them. The book encourages readers to think about the wider effect of their work by addressing the ethical and social aspects of data science in addition to its technical content. Readers will have a solid foundation in data science at the conclusion of the book, along with the know-how to take on challenging data problems and make significant contributions to the field.