A Coursera course on Machine Learning starts on 16 June

May 21, 2014
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(This article was first published on blog.RDataMining.com, and kindly contributed to R-bloggers)

A 10-week course on Machine Learning by Andrew Ng from Stanford University will start on Coursera on 16 June. Below are descriptions of the course picked up from Coursera.

The course provides a broad introduction to machine learning, data mining, and statistical pattern recognition. Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). (ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). (iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI).

The course will also draw from numerous case studies and applications, so that you’ll also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas.

See details and join the course at http://www.coursera.org/course/ml


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