good machine learning books

Architecting Data and Machine Learning Platforms - by Marco Tranquillin & Valliappa Lakshmanan & Firat Tekiner (Paperback)

Deep Learning - by Andrew Glassner (Paperback)

Intelligent System and Computing: Future Technologies - by Boris Vega (Hardcover)

Machine Learning Algorithms in Depth - by Vadim Smolyakov (Paperback)

Artificial Intelligence for Libraries - by Brady D Lund (Hardcover)

Artificial Intelligence: Concepts, Tools and Techniques - by Mitch Hoppe (Hardcover)

Optical Networks - 3rd Edition by Rajiv Ramaswami & Kumar Sivarajan & Galen Sasaki (Hardcover)

Intelligent Systems Handbook - by Boris Vega (Hardcover)

Optimization: An Introduction - (Studies in Systems, Decision and Control) by Libor Peka&#345 (Hardcover)

Hands-On Scikit-Learn for Machine Learning Applications - by David Paper (Paperback)

Artificial Intelligence Techniques in Power Systems - (Energy Engineering) by Kevin Warwick & Arthur Ekwue & Rag Aggarwal (Hardcover)

Blockchain Technology for Smart Grids - (Energy Engineering) (Hardcover)

Bioinformatics Algorithms - by Miguel Rocha & Pedro G Ferreira (Paperback)

Artificial Neural Networks: Advances and Applications - by John Hopkins (Hardcover)

Implementation of Self-Tuning Controllers - (Control, Robotics and Sensors) by K Warwick (Hardcover)

The Sustainability of Science - by Martin Farley (Hardcover)

Theories and Applications of Artificial Intelligence - by Mitch Hoppe (Hardcover)

Python: Practical Programming - by Cooper Webb (Hardcover)

How AI Works - by Ronald T Kneusel (Paperback)

Adventures from the Technology Underground - Annotated by William Gurstelle (Paperback)

The Quotable Feynman - by Richard P Feynman

Linux All-In-One for Dummies - 7th Edition by Richard Blum (Paperback)

Kerberos: The Definitive Guide - by Jason Garman (Paperback)

Applications of Deep Learning in Electromagnetics - (Electromagnetic Waves) by Maokun Li & Marco Salucci (Hardcover)