So others can also see the thought they put into the program, here's the actual ...

dofly · on May 10, 2018

Thanks. I was wondering about that. Do you know, by chance, what books or notes they might use?

epicureanideal · on May 10, 2018

I'm starting with gathering the book requirements for some of the electives which might be of interest to me...

For 85-712 COGNITIVE MODELING:

How Can the Human Mind Occur in the Physical Universe? 2009 Author: Anderson, John

ANSI Common Lisp 1996 Author: Graham, Paul

For 85-211 COGNITIVE PSYCH:

Cognitive Psychology and Its Implications 7TH 10 Author: Anderson, John

For 85-814 COGNITIVE NEUROSCIENCE:

No books listed.

For 85-421 LANGUAGE AND THOUGHT:

Language in Mind: An Introduction to Psycholinguistics 2014 Author: Sedivy, Julie

I'll update this with more books shortly.

For 15-386 Neural Computation:

From course website: http://www.cnbc.cmu.edu/~tai/nc17.html Trappenberg T.P. (TTP) Fundamentals of computational neuroscience, 2nd edition, Oxford University Press 2009 (required/recommended). Hertz J, Krogh A, Palmer RG (HKP) Introduction to the theory of neural computation., Addison Wesley 1991 (reference).

For 15-150: Principles of Functional Computation:

From course website http://www.cs.cmu.edu/~15150/ There is no required textbook for the course. All material we expect you to be familiar with will be covered in sufficient detail in the lectures and lecture notes. There is an optional (and free!) text which some students find useful, called Programming In Standard ML (PSML). This book is based on the lecture notes for the predecessor to this course, 15-212.

For CS 15-122: Principles of Imperative Computation:

http://www.cs.cmu.edu/~15122/syllabus.shtml No textbook, but uses C, Emacs, Linux.

For 15-381: Introduction to AI Representation and Problem Solving:

Artificial Intelligence: A Modern Approach, Third Edition (Typical at most schools for teaching Intro to AI/ML.)

For 10-401: Introduction to Machine Learning

Machine Learning, Tom Mitchell. (optional) Pattern Recognition and Machine Learning, Christopher Bishop. (optional) Machine Learning: A Probabilistic Perspective, Kevin P. Murphy, available online, (optional)

bytematic · on May 10, 2018

Sorry this isn't a super researched answer but most of the course titles can be googled to find a "course website" that will usually list that information or a syllabus