Cultural Analytics (MIT Press)
Friday, 30 October 2020

What analytical methods can we bring to bear on the astonishing scale of digital culture--the billions of photographs shared on social media  every day, the hundreds of millions of songs created by twenty million musicians on Soundcloud, the content of four billion Pinterest boards? In this book, Lev Manovich presents concepts and methods for computational analysis of cultural data.

<ASIN:0262037106>

Drawing on a decade of research and projects from his own lab, Manovich offers a gentle, nontechnical introduction to the core ideas of data analytics and discusses the ways that our society uses data and algorithms.

Author: Lev Manovich
Publisher: MIT Press
Date: October 2020
Pages: 336
ISBN: 978-0262037105
Print: 0262037106
Kindle: B084V7XLC7
Audience: General
Level: Introductory
Category: Data Science

 

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

 

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Deep Learning (No Starch Press)

Author: Andrew Glassner
Publisher: No Starch Press
Date: July 2021
Pages: 750
ISBN: 978-1718500723
Print: 1718500726
Kindle: ‎ B085BVWXNS
Audience: Developers interested in deep learning
Rating: Mike James
Reviewer: 5
A book on deep learning wtihout an equation in sight?



The Road to Azure Cost Governance

Author: Paola E. Annis et al
Publisher: Packt Publishing
Pages: 314
ISBN: 978-1803246444
Print: 1803246448
Kindle: B09NW2CTHX
Audience: Bill payers
Rating: 4.5
Reviewer: Ian Stirk

This book aims to help you reduce your Azure costs, how does it fare?


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