{"repo":"jmshea/Foundations-of-Data-Science-with-Python","free":true,"listed":false,"github":"https://github.com/jmshea/Foundations-of-Data-Science-with-Python","clone":"git clone https://github.com/jmshea/Foundations-of-Data-Science-with-Python.git","description":"Interactive flashcards and quizzes, as well as additional tutorials, animations, and code, for \"Foundations of Data Science with Python\" by John M. Shea","language":"Jupyter Notebook","stars":36,"topics":["data-science","data-visualization","probability","statistics","statistics-course"],"license":null,"category":"analytics","readme_excerpt":"Foundations of Data Science with Python by John M. Shea Learn data visualization, statistics, probability, and dimensionality reduction using a computational-first approach, without giving up mathematical rigor. A great textbook for an Introduction to Data Science or Engineering Statistics class. Buy on Amazon . [Affiliate link] This repository is the source for the book's website (fdsp.net). About the book This book is an introduction to the foundations of data science, including data visualization, statistics, probability, and dimensionality reduction. This book is targeted toward engineers and scientists, but it should be easily accessible to anyone who knows basic calculus and the basics of computer programming. By leveraging this background knowledge, this book fits a unique niche in the books on data science and statistics: This book applies a modern, computational approach to work with data , and in particular, uses simulations (an approach called resampling ) to answer statistical questions. Many books on statistics (especially those for engineers) teach a theoretical approach to answering statistical questions that many learners find difficult to understand. Most learners can easily understand how resampling works in contrast to some arcane formula. This text provides a basic, but rigorous, introduction to probability and its application to statistics. Some of the other books that use the resampling approach to statistics omit the mathematical foundations because the","default_branch":null,"files":null,"tree":[],"storefront":"/r/jmshea","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/jmshea/Foundations-of-Data-Science-with-Python/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}