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Machine Learning is one of the ten free courses being offered to the public through Stanford Engineering Everywhere. The course belongs to the Artificial Intelligence series and is taught by Andrew Ng, Assistant Professor of Stanford University's Computer Science Department. This course provides a broad introduction to machine...
Machine Learning is one of the ten free courses being offered to the public through Stanford Engineering Everywhere. The course belongs to the Artificial Intelligence series and is taught by Andrew Ng, Assistant Professor of Stanford University's Computer Science Department. This course provides a broad introduction to machine learning and statistical pattern recognition.
Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (clustering, dimensionality reduction, kernel methods); learning theory (bias/variance tradeoffs; VC theory; large margins); reinforcement learning and adaptive control.
The course will also discuss recent applications of machine learning, such as to robotic control, data mining, autonomous navigation, bioinformatics, speech recognition, and text and web data processing.
College General Ed,
College Lower Division,
College Upper Division,
Not specified at this time
Technical Requirements: Lecture videos are offered via Silverlight, iTunes, YouTube, and downloadable .wmv and .mp4 torrents. Course materials in the form of .pdf files are also available for download.
It is a very rich material which covers the main concepts about Learning Machine. I wouldn't suggest this material in a self study context because, in my opinion, a good mathematical background is needed.