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Pandas for Data Wrangling – tutorial, cheat sheet

Pandas is a powerful python library for data manipulation. It requires limited query level optimisation as its functions can perform rapid data...

Data Wrangling – preprocessing

Data Wrangling(preprocessing, prep, etc) is the most important and time consuming part of any data science project. Depending on the quality of...

Open source Data science libraries – AI, ML, NLP

Scikit-learn  is a free software machine learning library for the Python programming language. It features various classification, regression and clustering algorithms including...

Open source Data science Tools – Anaconda, Spyder, Python

The open-source Anaconda Distribution is the easiest way to perform Python/R data science and machine learning on Linux, Windows, and Mac OS X....

Youtube – MIT OpenCourseWare – Statistics lecture series

MIT 18.650 Statistics for Applications, Fall 2016 View the complete course: http://ocw.mit.edu/18-650F16 Instructor: Philippe Rigollet This course offers an in-depth the theoretical...

YouTube tutorials – Stanford NLP Lecture series

Stanford Lecture Collection | Natural Language Processing with Deep Learning (Winter 2017). https://www.youtube.com/playlist?list=PL3FW7Lu3i5Jsnh1rnUwq_TcylNr7EkRe6

YouTube tutorials – Linear algebra – Matrices, Vectors, Eigenvectors

Very good free YouTube tutorials on Linear algebra - matrices, vectors, eigenvectors, etc. Essence of linear algebra. A...

Udemy Online courses – ML, AI, NLP using Python

Machine Learning A-Z™: Hands-On Python & R In Data Science Learn to create Machine Learning Algorithms in...

Richard Socher – Using RNN for NLP

Abstract - Semantic word spaces have been very useful but cannot express the meaning of longer phrases in a principled way. Further...

Geoffrey Hinton, Father of Deep Learning, research articles page

http://www.cs.toronto.edu/~hinton/papers.html One of his earlier articles written in 1986!Learning internal representations by error propagation. http://www.cs.toronto.edu/~hinton/absps/pdp8.pdf Another one...