Modern Algorithms of Cluster Analysis (Springer)
Monday, 17 June 2019

This book provides a basic understanding of the formal concepts of the cluster, clustering, partition, and cluster analysis. Authors Slawomir Wierzchoń and Mieczyslaw Klopotek explain feature-based, graph-based and spectral clustering methods and discuss their formal similarities and differences. They also provide an overview of approaches to handling large collections of objects in a reasonable time, including grid-based methods, sampling methods, parallelization via Map-Reduce, usage of tree-structures, random projections and various heuristic approaches.

<ASIN: 3319887521>

Author: Slawomir Wierzchoń and Mieczyslaw Klopotek
Publisher: Springer
Date: June 2019
Pages: 444
ISBN: 978-3319887524
Print: 3319887521
Kindle: B078Q1YL76
Audience: Data scientists
Level: Intermediate/Advanced
Category: Data Science 


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


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C Programming Language (2e)

Author: Brian W. Kernighan, Dennis M. Ritchie
Publisher: Prentice Hall
Pages: 272
ISBN: 978-0131103627
Print: 0131103628
Kindle: B009ZUZ9FW
Audience: Programmers who know what K&R is
Rating: 5, but with reservations
Reviewer: Harry Fairhead

This is a classic but not everyone appreciates this p [ ... ]

Machine Learning in Python

Author:  Michael Bowles 
Publisher: Wiley
Pages: 360
ISBN: 978-1118961742
Print: 1118961749
Kindle: B00VOY1I98
Audience: Python programmers with data to analyze
Rating: 3.5
Reviewer:  Mike James 

Python is a good language to use to implement machine learning, but what exactly [ ... ]

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