Handbook of Big Data (Chapman & Hall)
Friday, 16 August 2019

This book provides a state-of-the-art overview of the analysis of large-scale datasets. Featuring contributions from well-known experts in statistics and computer science, authors Peter Bühlmann, Petros Drineas, Michael Kane and Mark van der Laan present a carefully curated collection of techniques from both industry and academia. The text is designed to instill a working understanding of key statistical and computing ideas that can be readily applied in research and practice.

<ASIN:1482249073>

 

Authors: Peter Bühlmann, Petros Drineas, Michael Kane and Mark van der Laan
Publisher: Chapman & Hall/CRC Press
Date: August 2019
Pages: 480
ISBN: 978-0367330736
Print: 1482249073
Kindle: B01BV3YV36
Audience: Developers/Students interested in big data
Level: Intermediate/Advanced
Category: Data Science 

handbigdata

 

  • Describes modern, scalable approaches for analyzing increasingly large datasets
  • Defines the underlying concepts of the available analytical tools and techniques
  • Details intercommunity advances in computational statistics and machine learning

 

 

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

 

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Zombie Scrum Survival Guide (Addison-Wesley)

Author: Christiaan Verwijs, Johannes Schartau and Barry Overeem
Publisher: Addison-Wesley Professional
Date: November 2020
Pages: 200
ISBN: 978-0136523260
Print: 0136523269
Kindle: ‎ B08F5GY39V
Audience: Scrum developers
Rating: 5
Reviewer: Kay Ewbank

The idea behind this book is a fascinating [ ... ]



TinyML: Machine Learning with TensorFlow Lite

Authors: Pete Warden and Daniel Situnayake
Publisher: O'Reilly
Date: December 2019
Pages: 504
ISBN: 978-1492052043
Print: 1492052043
Kindle: B082TY3SX7
Audience: Developers interested in machine learning
Rating: 5, but see reservations
Reviewer: Harry Fairhead
Can such small machines really do ML?


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