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8/17/2019 Artificial Intelligence Links
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Artificial Intelligence
This is going to be a list of resources for learning the required topics to be considered
knowledgeable in the field of artificial intelligence. This will be everything I can find,
including textbooks, researchers, papers, courses, video series, and notes. Some of thesebooks can be put in other categories, but I just put them in what I would see most.
Basics
Programming
● Learning how to program
- https://www.edx.org/course/introduction-computer-science-harvardx-cs50x
● Python
- https://developers.google.com/edu/python/
- http://learnpythonthehardway.org/
- https://www.coursera.org/specializations/python ● R
- https://www.coursera.org/learn/r-programming
Mathematics
● http://www.amazon.com/Introduction-Algorithms-3rd-Edition-Press/dp/0262033844
● http://inst.eecs.berkeley.edu/~cs70/sp16/
● https://www.coursera.org/learn/calculus1
● https://www.coursera.org/learn/advanced-calculus
● https://www.coursera.org/course/matrix
● https://www.edx.org/course/effective-thinking-through-mathematics-utaustinx-ut-9
-1x
● https://www.khanacademy.org/math/linear-algebra
● http://www.amazon.com/Applied-Linear-Algebra-Lorenzo-Sadun/dp/0821844415
Statistics
● https://www.edx.org/course/introduction-probability-science-mitx-6-041x-1
● http://www.amazon.com/Introduction-Probability-Edition-Dimitri-Bertsekas/dp/188
652923X
Data Science
● https://www.coursera.org/specializations/jhu-data-science
● https://courses.edx.org/courses/BerkeleyX/CS100.1x/1T2015/fbe63aa3c95948e391
2fa128aedec27d/
● https://lagunita.stanford.edu/courses/Engineering/db/2014_1/about
● https://www.coursera.org/learn/intro-to-big-data
http://www.amazon.com/Introduction-Probability-Edition-Dimitri-Bertsekas/dp/188652923Xhttp://www.amazon.com/Introduction-Probability-Edition-Dimitri-Bertsekas/dp/188652923Xhttps://www.khanacademy.org/math/linear-algebrahttps://www.khanacademy.org/math/linear-algebrahttps://www.edx.org/course/effective-thinking-through-mathematics-utaustinx-ut-9-01xhttps://www.edx.org/course/effective-thinking-through-mathematics-utaustinx-ut-9-01xhttps://www.coursera.org/learn/advanced-calculushttps://www.coursera.org/learn/advanced-calculushttps://www.coursera.org/learn/calculus1https://www.coursera.org/learn/calculus1http://inst.eecs.berkeley.edu/~cs70/sp16/http://inst.eecs.berkeley.edu/~cs70/sp16/https://www.coursera.org/specializations/pythonhttp://learnpythonthehardway.org/https://developers.google.com/edu/python/https://www.edx.org/course/introduction-computer-science-harvardx-cs50xhttps://www.edx.org/course/introduction-computer-science-harvardx-cs50xhttps://www.coursera.org/learn/intro-to-big-datahttps://lagunita.stanford.edu/courses/Engineering/db/2014_1/abouthttps://courses.edx.org/courses/BerkeleyX/CS100.1x/1T2015/fbe63aa3c95948e3912fa128aedec27d/https://courses.edx.org/courses/BerkeleyX/CS100.1x/1T2015/fbe63aa3c95948e3912fa128aedec27d/https://www.coursera.org/specializations/jhu-data-sciencehttp://www.amazon.com/Introduction-Probability-Edition-Dimitri-Bertsekas/dp/188652923Xhttp://www.amazon.com/Introduction-Probability-Edition-Dimitri-Bertsekas/dp/188652923Xhttps://www.edx.org/course/introduction-probability-science-mitx-6-041x-1http://www.amazon.com/Applied-Linear-Algebra-Lorenzo-Sadun/dp/0821844415https://www.khanacademy.org/math/linear-algebrahttps://www.edx.org/course/effective-thinking-through-mathematics-utaustinx-ut-9-01xhttps://www.edx.org/course/effective-thinking-through-mathematics-utaustinx-ut-9-01xhttps://www.coursera.org/course/matrixhttps://www.coursera.org/learn/advanced-calculushttps://www.coursera.org/learn/calculus1http://inst.eecs.berkeley.edu/~cs70/sp16/http://www.amazon.com/Introduction-Algorithms-3rd-Edition-Press/dp/0262033844https://www.coursera.org/learn/r-programminghttps://www.coursera.org/specializations/pythonhttp://learnpythonthehardway.org/https://developers.google.com/edu/python/https://www.edx.org/course/introduction-computer-science-harvardx-cs50x
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● https://www.coursera.org/course/patterndiscovery
● https://www.coursera.org/course/algs4partI
● https://www.coursera.org/course/algs4partII
Machine Learning
● https://www.coursera.org/course/neuralnets ● https://www.youtube.com/watch?v=UzxYlbK2c7E
● http://videolectures.net/mackay_course_01/
● http://rll.berkeley.edu/deeprlcourse/
● https://www.coursera.org/course/pgm
● http://webdocs.cs.ualberta.ca/~sutton/book/the-book.html
● http://rll.berkeley.edu/deeprlcourse/docs/ng-thesis.pdf
● http://statweb.stanford.edu/~tibs/ElemStatLearn/
● https://courses.edx.org/courses/BerkeleyX/CS190.1x/1T2015/info
● https://lagunita.stanford.edu/courses/HumanitiesSciences/StatLearning/Winter201
6/about ● http://www.cs.ubc.ca/~murphyk/MLbook/index.html
● https://www.coursera.org/learn/practical-machine-learning
● http://archive.ics.uci.edu/ml/
● https://www.coursera.org/specializations/machine-learning
Deep Learning
● http://cilvr.nyu.edu/doku.php?id=deeplearning:slides:start
● http://www.deeplearningbook.org/
● https://www.udacity.com/course/deep-learning--ud730
● https://sites.google.com/site/deeplearningsummerschool/home ● http://cs224d.stanford.edu/
●
Cognitive Thinking
● http://www.amazon.com/Fundamentals-Cognitive-Psychology-Ronald-Kellogg/dp/1
483347583/ref=pd_sim_14_2?ie=UTF8&dpID=51HGdwbnU0L&dpSrc=sims&preST=_
AC_UL160_SR129%2C160_&refRID=0W1X5MSBH6YEYVKS75QZ
● http://www.amazon.com/Constructing-Language-Usage-Based-Theory-Acquisition/d
p/0674017641
● http://www.amazon.com/Action-Perception-Representation-Mind-Alva/dp/0262640
635
● http://www.amazon.com/The-Vision-Revolution-Overturns-Everything/dp/19352517
67
● http://www.amazon.com/On-Intelligence-Jeff-Hawkins/dp/0805074562
● http://mind.sourceforge.net/theory5.html
Neuroscience
http://mind.sourceforge.net/theory5.htmlhttp://www.amazon.com/On-Intelligence-Jeff-Hawkins/dp/0805074562http://www.amazon.com/The-Vision-Revolution-Overturns-Everything/dp/1935251767http://www.amazon.com/The-Vision-Revolution-Overturns-Everything/dp/1935251767http://www.amazon.com/Action-Perception-Representation-Mind-Alva/dp/0262640635http://www.amazon.com/Action-Perception-Representation-Mind-Alva/dp/0262640635http://www.amazon.com/Constructing-Language-Usage-Based-Theory-Acquisition/dp/0674017641http://www.amazon.com/Constructing-Language-Usage-Based-Theory-Acquisition/dp/0674017641http://www.amazon.com/Fundamentals-Cognitive-Psychology-Ronald-Kellogg/dp/1483347583/ref=pd_sim_14_2?ie=UTF8&dpID=51HGdwbnU0L&dpSrc=sims&preST=_AC_UL160_SR129%2C160_&refRID=0W1X5MSBH6YEYVKS75QZhttp://www.amazon.com/Fundamentals-Cognitive-Psychology-Ronald-Kellogg/dp/1483347583/ref=pd_sim_14_2?ie=UTF8&dpID=51HGdwbnU0L&dpSrc=sims&preST=_AC_UL160_SR129%2C160_&refRID=0W1X5MSBH6YEYVKS75QZhttp://www.amazon.com/Fundamentals-Cognitive-Psychology-Ronald-Kellogg/dp/1483347583/ref=pd_sim_14_2?ie=UTF8&dpID=51HGdwbnU0L&dpSrc=sims&preST=_AC_UL160_SR129%2C160_&refRID=0W1X5MSBH6YEYVKS75QZhttp://cs224d.stanford.edu/https://sites.google.com/site/deeplearningsummerschool/homehttps://www.udacity.com/course/deep-learning--ud730http://www.deeplearningbook.org/http://cilvr.nyu.edu/doku.php?id=deeplearning:slides:starthttps://www.coursera.org/specializations/machine-learninghttp://archive.ics.uci.edu/ml/https://www.coursera.org/learn/practical-machine-learninghttp://www.cs.ubc.ca/~murphyk/MLbook/index.htmlhttps://lagunita.stanford.edu/courses/HumanitiesSciences/StatLearning/Winter2016/abouthttps://lagunita.stanford.edu/courses/HumanitiesSciences/StatLearning/Winter2016/abouthttps://courses.edx.org/courses/BerkeleyX/CS190.1x/1T2015/infohttp://statweb.stanford.edu/~tibs/ElemStatLearn/http://rll.berkeley.edu/deeprlcourse/docs/ng-thesis.pdfhttp://webdocs.cs.ualberta.ca/~sutton/book/the-book.htmlhttps://www.coursera.org/course/pgmhttp://rll.berkeley.edu/deeprlcourse/http://videolectures.net/mackay_course_01/https://www.youtube.com/watch?v=UzxYlbK2c7Ehttps://www.coursera.org/course/neuralnetshttps://www.coursera.org/course/algs4partIIhttps://www.coursera.org/course/algs4partIhttps://www.coursera.org/course/patterndiscovery
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● http://www.amazon.com/Neuroscience-Exploring-Mark-F-Bear/dp/0781778174/ref=
pd_sim_14_3?ie=UTF8&dpID=51JUiv62mEL&dpSrc=sims&preST=_AC_UL160_SR124
%2C160_&refRID=1NGD47SA7VJWJTTD9WFM
● http://www.amazon.com/Developmental-Cognitive-Neuroscience-Mark-Johnson/dp/
1444330853
Artificial Intelligence
● https://www.edx.org/course/artificial-intelligence-uc-berkeleyx-cs188-1x
● http://ai.neocities.org/AiSteps.html
● https://www.udacity.com/course/intro-to-artificial-intelligence--cs271
● http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-034-artif
icial-intelligence-fall-2010/
Researchers and People to know
● https://en.wikipedia.org/wiki/Andrew_Ng
● https://en.wikipedia.org/wiki/Geoffrey_Hinton ● https://en.wikipedia.org/wiki/Nick_Bostrom
Textbooks/Papers
● Bayesian Reasoning and Machine Learning - David Barber
● Where Do Features Come From? Geoffrey Hinton
● Modeling Documents With a Deep Boltzmann Machine - Geoffrey Hinton, Nitish
Srivastava, and Ruslan Salakhutdinov
● Distilling the Knowledge in a Neural Network - Geoffrey Hinton, Oriol Vinyalis, and
Jeff Dean
● Grammar as a Foreign Language - Hinton plus others● Information Science and Statistics - Christopher Bishop
● Information Theory, Inference, and Learning Algorithms - David MacKay
● An Introduction into Statistical Learning with Applications in R
● Dropout: A Simple Way to Prevent Neural Networks from Overfitting - Toronto CS
● Machine Learning - Peter Flach
● Building Machine Learning Systems with Python - Willi Richert
● To Recognize Shapes, First Learn to Generate Images - Hinton
● Deep Learning - LeCun, Bengio, Hinton
● A Fast Learning Algorithm for Deep Belief Nets - Hinton, Teh, Osindero
● Speech Recognition with Deep Recurrent Neural Networks - Hinton, Mohammed,
Graves
● Reducing the Dimensionality of Data with Neural Networks - Hinton, Salakhuditinov
● Superintelligence Paths Dangers Stragies - Bostrom
Other
● https://wiki.python.org/moin/PythonForArtificialIntelligence
● https://www.tensorflow.org/
● http://frnsys.com/ai_notes/
http://frnsys.com/ai_notes/https://www.tensorflow.org/https://wiki.python.org/moin/PythonForArtificialIntelligencehttps://en.wikipedia.org/wiki/Nick_Bostromhttps://en.wikipedia.org/wiki/Geoffrey_Hintonhttps://en.wikipedia.org/wiki/Andrew_Nghttp://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-034-artificial-intelligence-fall-2010/http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-034-artificial-intelligence-fall-2010/https://www.udacity.com/course/intro-to-artificial-intelligence--cs271http://ai.neocities.org/AiSteps.htmlhttps://www.edx.org/course/artificial-intelligence-uc-berkeleyx-cs188-1xhttp://www.amazon.com/Developmental-Cognitive-Neuroscience-Mark-Johnson/dp/1444330853http://www.amazon.com/Developmental-Cognitive-Neuroscience-Mark-Johnson/dp/1444330853http://www.amazon.com/Neuroscience-Exploring-Mark-F-Bear/dp/0781778174/ref=pd_sim_14_3?ie=UTF8&dpID=51JUiv62mEL&dpSrc=sims&preST=_AC_UL160_SR124%2C160_&refRID=1NGD47SA7VJWJTTD9WFMhttp://www.amazon.com/Neuroscience-Exploring-Mark-F-Bear/dp/0781778174/ref=pd_sim_14_3?ie=UTF8&dpID=51JUiv62mEL&dpSrc=sims&preST=_AC_UL160_SR124%2C160_&refRID=1NGD47SA7VJWJTTD9WFMhttp://www.amazon.com/Neuroscience-Exploring-Mark-F-Bear/dp/0781778174/ref=pd_sim_14_3?ie=UTF8&dpID=51JUiv62mEL&dpSrc=sims&preST=_AC_UL160_SR124%2C160_&refRID=1NGD47SA7VJWJTTD9WFM
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● https://books.google.com/books?uid=111815788291054011027&as_coll=1012&sour
ce=gbs_lp_bookshelf_list (HUGE AMOUNT OF TEXTBOOKS)
References
● http://wp.goertzel.org/agi-curriculum/
● https://docs.google.com/spreadsheets/d/1NSbURoynPVnOvSCtmaIX6zV8wl6n3ybacnNGMyb-v-0/edit#gid=0
● Wojciech Zaremba
https://www.reddit.com/user/mkdir_not_war
https://www.reddit.com/user/don_chow
https://www.reddit.com/user/AiHasBeenSolved
https://www.reddit.com/user/AiHasBeenSolvedhttps://www.reddit.com/user/don_chowhttps://www.reddit.com/user/mkdir_not_warhttps://docs.google.com/spreadsheets/d/1NSbURoynPVnOvSCtmaIX6zV8wl6n3ybacnNGMyb-v-0/edit#gid=0https://docs.google.com/spreadsheets/d/1NSbURoynPVnOvSCtmaIX6zV8wl6n3ybacnNGMyb-v-0/edit#gid=0http://wp.goertzel.org/agi-curriculum/https://books.google.com/books?uid=111815788291054011027&as_coll=1012&source=gbs_lp_bookshelf_listhttps://books.google.com/books?uid=111815788291054011027&as_coll=1012&source=gbs_lp_bookshelf_list