Reading List

Here you can find some of my preferred readings on AI 'n' ML.

Deep Learning Books

Deep Learning
Ian Goodfellow, Yoshua Bengio and Aaron Courville
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The Adolescence of Technology
Confronting and Overcoming the Risks of Powerful AI
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Deep Learning for Coders With Fastai and Pytorch: AI Applications Without a Phd
Jeremy Howard & Sylvain Gugger
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Neural Networks and Deep Learning
Michael Nielsen
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Deep Learning for Computer Vision with Python
Adrian Rosebrock
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TinyML: Machine Learning With Tensorflow Lite on Arduino and Ultra-Low-Power Microcontrollers
Pete Warden & Daniel Situnayake
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Practical Natural Language Processing
Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta & Harshit Surana
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Machine Learning & AI Books

A Thousand Brains: A New Theory of Intelligence
Jeff Hawkins
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Machina sapiens. L'algoritmo che ci ha rubato il segreto della conoscenza
Nello Cristianini
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Thinking, Fast and Slow
Daniel Kahneman
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Hands-On Machine Learning with Scikit-Learn & TensorFlow
Aurelien Geron
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Reinforcement Learning An Introduction (second edition)
Richard S. Sutton and Andrew G. Barto
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Artificial Intelligence: A Modern Approach
Stuart Russell & Peter Norvig
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Probably Approximately Correct
Leslie Valiant
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The Technological Singularity
Murray Shanahan
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Miscellaneous Books

Practical Python and OpenCV
Adrian Rosebrock
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C e C++
Carlo A. Mazzone
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Computing: A Concise History
Paul E. Ceruzzi
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How Linux Works
Brian Ward
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Il metodo geniale
Giulio Deangeli
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But How Do It Know?
J.Clasrk Scott
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Infinite Powers: How Calculus Reveals the Secrets of the Universe
Steven Strogatz
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Python 3: Guida tascabile al linguaggio di Google, Star Wars e la NASA
Marco Beri
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Reti Domestiche
Pier Calderan
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Online Tutorials and Courses

TensorFlow Official Tutorial
Google
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FastAI
Jeremy Howard & Co.
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Deep Learning Specialization
Andrew Ng
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Machine Learning A-Z™: Hands-On Python & R In Data Science
Kirill Eremenko, Hadelin de Ponteves
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3Blue1Brown
Grant Sanderson
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