aksh/cs-ai.md

• BOOKS
• AI
• Computational Formalisms
• Data Structures
• Graphs
• HMM
• Machine Learning
• NLP

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BOOKS

• The book "biological sequence analysis" by Durbin and Eddy.

NLP and ML

• https://mitpress.mit.edu/books/introduction-algorithms
• http://www.amazon.com/The-Art-Computer-Programming-Vol/dp/0201896834
• G. Bordogna, M. Pagani, and G. Pasi, Soft Computing for Information Retrieval on the Web. Springer Verlag, 2006.
• Indurkhya, N., and Damerau, F. Handbook Of Natural Language Processing, 2nd Edition CRC 2010
• Sebastiani, (2002) Machine learning in automated text categorization, ACM Computing Surveys, 34 (1), 1-47.
• On The Use of Fuzzy Rules to Text Document Classification: Tatiane M. Nogueira, Solange O. Rezende, Heloisa A. Camargo
• A fuzzy approach to classifying text documents, Liu , Song.

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AI

• https://wtvox.com/robotics/google-is-working-on-a-new-algorithm-thought-vectors/

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Computational Formalisms

• https://en.wikipedia.org/wiki/Satisfiability_modulo_theories
• https://en.wikipedia.org/wiki/Category:Computational_problems
• http://en.wikipedia.org/wiki/Category:Computational_science

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Data Structures

• Algorithms, Part I :: https://www.coursera.org/course/algs4partI
• https://en.wikipedia.org/wiki/Data_structure

Books

• The Algorithm Design Manual, Steven.S.Skiena - An excellent reference to algorithm design and many common data types.
• "The Art of Computer Programming", Donald Knuth.

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Graphs

• Hierarchical Scheduling of DAG Structured Computations on Manycore Processors with Dynamic Thread Grouping, Yinglong Xia, et al.

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HMM

• http://www.ece.ucsb.edu/Faculty/Rabiner/ece259/Reprints/tutorial%20on%20hmm%20and%20applications.pdf
• Computational biology, http://www.rosalind.info

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Machine Learning

• {Paper} : Evaluation of Deep Learning Frameworks.
• https://github.com/svaksha/Julia.jl/blob/master/AI.md#machine-learning
• https://github.com/svaksha/pythonidae/blob/master/AI.md#machine-learning
• https://github.com/hangtwenty/dive-into-machine-learning
• https://www.udacity.com/podcasts/linear-digressions
• https://soundcloud.com/oreilly-radar/sets/the-oreilly-data-show-podcast (feed here)
• http://www.thetalkingmachines.com/ways-to-listen
• http://www.partiallyderivative.com/

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NLP

• https://github.com/ftzeng/broca

Sentiment Analysis

• Front End Resources: Ajax Hacks : http://webmasters.stackexchange.com/questions/22338/why-not-ajaxify-entire-websites
• Back End Resources:
• http://www.elasticsearch.org/guide/reference/river/
• https://dev.twitter.com/programs/twitter-certified-products/products

NLTK

• NLTK trainer, https://bitbucket.org/japerk/nltk-trainer/src
• https://github.com/marcua/tweeql/
• http://streamhacker.com/2010/10/25/training-binary-text-classifiers-nltk-trainer/
• http://www.laurentluce.com/posts/twitter-sentiment-analysis-using-python-and-nltk/

Resources

• http://spaceandtim.es/opennews/broca
• Automated Job Description Text analyzers :
  • Textio
  • Joblint and the source code.

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