Wilkins, N. (2019). Artificial Intelligence: An Essential Beginner’s Guide to AI, Machine Learning, Robotics, The Internet of Things, Neural Networks, Deep Learning, Reinforcement Learning, and Our Future. Bravex Publications.

Amazon link: [www.amazon.com/Artificial-Intelligence-Essential-Beginners-Reinforcement/dp/1950922510](https://www.amazon.com/Artificial-Intelligence-Essential-Beginners-Reinforcement/dp/1950922510) 

AI: An Essential Beginner's Guide

Russell, S. J. (2016). Artificial intelligence: a modern approach. Harlow: Pearson.

PDF Link: [www.cin.ufpe.br/~tfl2/artificial-intelligence-modern-approach.9780131038059.25368.pdf](https://www.cin.ufpe.br/~tfl2/artificial-intelligence-modern-approach.9780131038059.25368.pdf) 

AI: A Modern Approach

- Artificial Intelligence: A Modern Approach
- Artificial Intelligence: An Essential Beginner’s Guide to AI, Machine Learning, Robotics, The Internet of Things, Neural Networks, Deep Learning, Reinforcement Learning, and Our Future

University of Michigan - Ann Arbor

The list of helpful broad references about AI is categorized as follows:
1- AI books
2- AI online courses
3- AI research papers
4- Images related to AI
5- AI videos

Artifical Intelligence references

Artificial Intelligence Books

In the dominant machine learning approach, rather than designing explicit step-by-step rules to map inputs to outputs, practitioners define a flexible program whose behavior is governed by a set of adjustable parameters. By presenting this program with a large dataset of examples and labels, a learning algorithm determines the optimal parameter values that maximize the model's performance on the desired task.

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