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Although Stanford Online was founded in 1995 through the Stanford Center for Professional Development, [7] it has a history that spans back to the late 1960s. [8] The start of the center began in part to the Engineering School within the University [8] which created the university's first TV network as a new digital medium for students to take professional online courses and earn academic ...
Open edX platform is the open-source platform software developed by edX and made freely available to other institutions of higher learning that want to make similar offerings. On June 1, 2013, edX open sourced its entire platform. [40] The source code can be found on GitHub.
Statistical learning theory is a framework for machine learning drawing from the fields of statistics and functional analysis. [ 1 ] [ 2 ] [ 3 ] Statistical learning theory deals with the statistical inference problem of finding a predictive function based on data.
The Open edX platform is the open-source software, originally developed by Piotr Mitros, [2] [3] whose development led to the creation of the edX organization. On June 1, 2013, edX open sourced the platform, naming it Open edX to distinguish it from the organization itself. [4] The source code can be found on GitHub.
Udacity is the outgrowth of free computer science classes offered in 2011 through Stanford University. [9] Thrun has stated he hopes half a million students will enroll, after an enrollment of 160,000 students in the predecessor course at Stanford, Introduction to Artificial Intelligence, [10] and 90,000 students had enrolled in the initial two classes as of March 2012.
In statistics, multivariate adaptive regression splines (MARS) is a form of regression analysis introduced by Jerome H. Friedman in 1991. [1] It is a non-parametric regression technique and can be seen as an extension of linear models that automatically models nonlinearities and interactions between variables.
An Introduction to Computational Learning Theory. MIT Press, 1994. A textbook. M. Mohri, A. Rostamizadeh, and A. Talwalkar. Foundations of Machine Learning. MIT Press, 2018. Chapter 2 contains a detailed treatment of PAC-learnability. Readable through open access from the publisher. D. Haussler.
Trevor John Hastie (born 27 June 1953) is an American statistician and computer scientist. He is currently serving as the John A. Overdeck Professor of Mathematical Sciences and Professor of Statistics at Stanford University. [1]