Foundations of Data Science with Python (CRC Press)
Wednesday, 13 March 2024

This book introduces the fundamentals of data science, including data manipulation and visualization, probability, statistics, and dimensionality reduction. John M. Shea 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.

The 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.

Author: John M. Shea
Publisher: Chapman and Hall/CRC
Date: February 2024
Pages: 502
ISBN: 978-1032350424
Print: 1032350423
Kindle: ‎ B0CTCQR2BS
Audience: Python developers interested in data science
Level: Intermediate
Category: Python and Data Science

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For recommendations of Python books see Books for Pythonistas and Python Books For Beginners in our Programmer's Bookshelf section.

For recommendations of books on data science see Reading Your Way Into Big Data in our Programmer's Bookshelf section.

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Pro Database Migration to Azure

Author: Kevin Kline et al
Publisher: Apress
Pages: 352
ISBN: 978-1484282298
Print: 1484282299
Kindle: B0B924H21P
Audience: Managers & architects
Rating: 4
Reviewer: Ian Stirk

This book aims to give you a holistic approach to migrating on-premise databases to Azure, how does it fare?



Grokking Machine Learning

Author: Luis G. Serrano
Publisher: Manning
Date: December 2021
Pages: 512
ISBN: 978-1617295911
Print: 1617295914
Kindle: B09LK7KBSL
Audience: Python developers interested in machine learning
Rating: 5
Reviewer: Mike James
Another book on machine learning - surely we have enough by now?


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