Beyond the Worst-Case Analysis of Algorithms (Cambridge University Press)
Monday, 01 March 2021

Worst-case analysis, the cornerstone of most algorithm courses is where an algorithm is assessed by its worst performance on any input of a given size. The purpose of this book is to popularize several alternatives to worst-case analysis and their most notable algorithmic applications, from clustering to linear programming to neural network training. Tim Roughgarden along with forty leading researchers have contributed introductions to different facets of this field, emphasizing the most important models and results, many of which are suitable for beginners to the concepts of computer science and machine learning.

<ASIN:1108494315>

 

Author: Tim Roughgarden (Editor)
Publisher: Cambridge University Press
Date: February 2021
Pages: 704
ISBN: 978-1108494311
Print: 1108494315
Kindle: B08GGCFMTB
Audience: Developers interested in computer science
Level: Intermediate/Advanced
Category: Theory & Techniques 

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Learning Progressive Web Apps

Author: John M Wargo
Publisher: Addison-Wesley
Pages: 272
ISBN: 978-0136484226
Print: 0136484220
Kindle: B084T4JK3S
Audience: Capable JavaScript programmers
Rating: 4.5
Reviewer: Ian Elliot
PWAs - I'm not even sure what they are?



Mathematics for Machine Learning

Authors: Marc Peter Deisenroth, Aldo Faisal and Cheng Soon Ong
Publisher: Cambridge University Press
Pages: 398
ISBN: 978-1108455145
Print: 110845514X
Kindle: B083M7DBP6
Audience: Developers interested in machine learning
Rating: 3.5
Reviewer: Mike James
Lots of people need to learn the math behind mach [ ... ]


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