Algorithms for Optimization (MIT Press)
Monday, 18 March 2019

This book offers a comprehensive introduction to optimization with a focus on practical algorithms. Authors Mykel J. Kochenderfer and Tim A. Wheeler approach optimization from an engineering perspective, where the objective is to design a system that optimizes a set of metrics subject to constraints. Readers will learn about computational approaches for a range of challenges, including searching high-dimensional spaces, handling problems where there are multiple competing objectives, and accommodating uncertainty in the metrics. The text provides concrete implementations in the Julia programming language.

 

Authors: Mykel J. Kochenderfer and Tim A. Wheeler
Publisher: MIT Press
Date: March 2019
Pages: 520
ISBN: 978-0262039420
Print: 0262039427
Kindle: B07PPDYLGV
Audience: Julia developers interested in optimization
Level: Intermediate/Advanced
Category: Theory & Techniques 

 

 

algopt

 

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Grokking Machine Learning

Author: Luis G. Serrano
Publisher: Manning
Date: December 2021
Pages: 512
ISBN: 978-1617295911
Print: 1617295914
Kindle: B09LK7KBSL
Audience: Python developers interested in machine learning
Rating: 5
Reviewer: Mike James
Another book on machine learning - surely we have enough by now?



Wild West To Agile (Addison-Wesley)

Author: Jim Highsmith
Publisher: Addison-Wesley
Pages: 304
ISBN: 978-0137961009
Print: 0137961006
Kindle: B0BXWP88KP
Audience: Adherents of Agile methodology
Rating: 4.5
Reviewer: Alex Denham

The subtitle of this book is Adventures in Software Development Evolution and Revolution and it is personal reminin [ ... ]


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