This is SIGAI's HackPack repository.
We keep resources on all things A.I. here that've been vetted by UCF's A.I. researchers and enthusiasts.
It has resources ranging from the very beginnings to the frontier of the field.
(A) == Advanced (N) == Novice (B) == Beginner (S) == Short (L) == Long
Building Machines That Learn and Think Like People -- (A, L) Lake, et. al
Find It Here: http://www.mit.edu/~tomeru/papers/machines_that_think.pdf
What separates a good researcher from a great researcher is intuition. Building that is hard but a good place to start is with books that ask good questions, talk about high-level concepts, and leave the technical details to the textbooks.
Godel, Escher, Bach: An Eternal Golden Braid -- Douglas Hofstadter
Mind Design II -- edited by John Haugeland
The Master Algorithm -- Pedro Domingos
The Society of Mind -- Marvin Minsky
The Emotion Machine -- Marvin Minsky
These will suit all of your technical needs. Note we don't detail the edition of the texts. Just get the latest one that's out - that's what we'd do if possible. After all, it's a fast-paced field.
Machine Learning: A Probabilistic Perspective -- Kevin Murphy
Artificial Intelligence: A Modern Approach -- Stuart Russell & Peter Norvig
Make Your Own Neural Network -- Tariq Rashid -- https://drive.google.com/drive/folders/0B65X3y3Tw2wYZXN3R2JORnBCQm8
Neural Networks And Deep Learning -- Michael Nielson -- http://neuralnetworksanddeeplearning.com/
Deep Learning -- Ian Goodfellow, et. al. -- http://www.deeplearningbook.org/
Coming Soon...
Coming Soon...