Data Science Using Python and R (Wiley)
Wednesday, 01 May 2019

This book is written for the general reader with no previous programming experience with an entire chapter is dedicated to learning the basics of Python and R. Then, each chapter presents step-by-step instructions and walkthroughs for solving data science problems using Python and R. Authors Chantal  and Daniel Larose cover topics including data preparation, exploratory data analysis, preparing to model the data, decision trees, model evaluation, misclassification costs, naïve Bayes classification, neural networks, clustering, regression modeling, dimension reduction, and association rules mining.Topics such as random forests and general linear models are also included. 

<ASIN:1119526817>

 

Author: Chantal D. Larose and Daniel T. Larose
Publisher: Wiley
Date: April 2019
Pages: 240
ISBN: 978-1119526810
Print: 1119526817
Kindle: B07NQZF8W2
Audience: would-be data scientists
Level: Introductory/Intermediate
Category: Data Science and Python

 

For recommendations of Python books see Books for Pythonistas and Python Books For Beginners in our Programmer's Bookshelf section. For recommendations of data mining books, see Reading Your Way Into Big Data in our Programmer's Bookshelf section.

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Closure: The Definitive Guide

Author: Michael Bolin
Publisher: O'Reilly, 2010
Pages: 592
ISBN: 978-1449381875
Print: 1449381871
Kindle: B0046RERYI
Audience: Existing and potential users of Closure
Rating: 4
Reviewed by: Mike James 


Closure is Google's very strange JavaScript compiler - does this book succeed in demystify [ ... ]



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Author: Nicholas H. Tollervey
Publisher: O'Reilly
Pages:206
ISBN: 978-1491972731
Print: 1491972734
Kindle:B075X49VVH
Audience: Python developers
Rating: 2
Reviewer: Harry Fairhead

Micropython seems to be eating the microcontroller world and learning it seems like a good idea.


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