Data Science Using Python and R (Wiley)
Wednesday, 07 August 2019

This book is written for the general reader with no previous analytics or programming experience. Authors Chantal D. Larose and Daniel T. Larose start with a chapter on the basics of Python and R, followed by chapters presenting step-by-step instructions and walkthroughs for solving data science problems using Python and R. Topics covered include 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.

 

Author: Chantal D. Larose and Daniel T. Larose
Publisher: Wiley
Date: April 2019
Pages: 240
ISBN: 978-1119526810
Print: 1119526817
Kindle: B07NQZF8W2
Audience: people interested in data science
Level: Intermediate
Category: Data Science

 

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

 

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C++ Programming, 7th Ed (In Easy Steps)

Author: Mike McGrath
Publisher: In Easy Steps
Date: April 2022
Pages: 192
ISBN: 9781787910379
Print: 1787910377
Kindle: B0F9LDHDBG
Audience: Developers wanting to learn C++
Rating: 4
Reviewer: Mike James

This is the 7th edition of a slim book on C++. Can you really learn C++ in easy steps?



Balancing Coupling in Software Design

Author: Vlad Khononov
Publisher: Addison-Wesley
Date: October 2024
Pages: 320
ISBN: 978-0137353484
Print: 0137353480
Kindle: B09RV3Z3TP
Audience: General
Rating: 4.5
Reviewer: Kay Ewbank

This book looks in detail at coupling, the degree of interdependence between software modules, and how to use coupling  [ ... ]


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