Introduction to Quantum Algorithms via Linear Algebra, 2nd Ed (MIT Press)
Friday, 30 April 2021

This book explains quantum computing in terms of elementary linear algebra, emphasizing computation and algorithms and requiring no background in physics. Richard J. Lipton and Kenneth W. Regan's book is concise but comprehensive, covering many key algorithms. It is mathematically rigorous but requires minimal background and assumes no knowledge of quantum theory or quantum mechanics. The book explains quantum computation in terms of elementary linear algebra; it assumes the reader will have some familiarity with vectors, matrices, and their basic properties, but offers a review of the relevant material from linear algebra.

<ASIN:0262045257>

 

Authors: Richard J. Lipton and Kenneth W. Regan
Publisher: The MIT Press
Date: April 2021
Pages: 269
ISBN: 978-0262045254
Print: 0262045257
Kindle: B08CTFBB78
Audience: Students or developers interested in quantum computing
Level: Intermediate/Advanced
Category: Mathematics

 

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Machine Learning with Python for Everyone

Author: Mark Fenner
Publisher: Addison-Wesley
Pages: 592
ISBN: 978-0134845623
Print: 0134845625
Kindle: B07VRSJ1GB
Audience: AI Beginners
Rating: 3
Reviewer: Mike James
A book that claims "for everyone" is promising a lot.



Python Machine Learning, 3rd Ed

Authors: Sebastian Raschka and Vahid Mirjalili
Publisher: Packt
Date: December 2019
Pages: 770
ISBN: 978-1789955750
Print: 1789955750
Kindle: B07VBLX2W7
Audience: Python devs interested in ML
Rating: 5
Reviewer: Mike James
A new edition of a good book on ML is worth a close look.


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