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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 foundations for statistical methods that are…
Stanford Lecture Collection | Natural Language Processing with Deep Learning (Winter 2017).
Very good free YouTube tutorials on Linear algebra – matrices, vectors, eigenvectors, etc. Essence of linear algebra. A geometric understanding of matrices, determinants, eigen-stuffs and more. Home page:…
Machine Learning A-Z™: Hands-On Python & R In Data Science Learn to create Machine Learning Algorithms in Python and R from two Data Science experts. Code templates included.…
Abstract – Semantic word spaces have been very useful but cannot express the meaning of longer phrases in a principled way. Further progress towards understanding compositionality in tasks…
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 of his earlier articles, very interesting and written in 1992. How neural…
Abstract – We propose a new method to quickly and accurately predict 3D positions of body joints from a single depth image, using no temporal information. We take…
https://www.kdnuggets.com/ https://towardsdatascience.com/ https://www.analyticsvidhya.com/ https://www.kaggle.com/ https://www.datacamp.com/community/data-science-cheatsheets
There are a large no of free books available online to learn the basics of data science. Very good to start with before considering more advanced books. Some…
Objective Observe and improve the results of applying NLP algorithms on FOMC meeting minutes to predict Fed Fund rate decision (hike, no hike, cut). Data and variations Fed…
Objective Observe and improve the results of running multiple linear regression and random forest algorithms on macroeconomic data to predict currency prices. Data UK, EU and US monthly…
