Artificial Intelligence: Machine Learning
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MERLOT II




        

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Artificial Intelligence: Machine Learning

        

Artificial Intelligence: Machine Learning

Logo for Artificial Intelligence: Machine Learning
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... More
Material Type: Online Course
Technical Format: Video
Date Added to MERLOT: November 20, 2008
Date Modified in MERLOT: September 16, 2009
Author:
Send email to see-information@lists.stanford.edu
Keywords: Dimensionality Reduction, Parametric Learning, Autonomous Navigation, Learning Theory, Adaptive Control, Stanford University, Vector Machines, Web Data Processing, Robotic Control, Andrew Ng, Statistical Pattern Recognition, Kernal Methods, Data Mining, Neural Networks, Artificial Intelligence, Machine Learning, VC Theory, Clustering, Stanford Engineering Everywhere, Supervised Learning, Speech Recognition

Quality

  • Reviewed by members of Editorial board for inclusion in MERLOT.
    Editor Review
    Very good quality; in queue to be peer reviewed
    avg: 5 rating
  • User review 4 average rating
  • User Rating: 4 user rating
  • Discussion (1 Comment)
  • Learning Exercises (none)
  • Personal Collections (1)
  • Accessibility Info (none)

About

Primary Audience: High School, College General Ed, College Lower Division, College Upper Division, Graduate School, Professional
Mobile Compatibility: 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.
Language: English
Material Version: First Release
Cost Involved: no
Source Code Available: no
Accessiblity Information Available: no
Creative Commons: Creative Commons License
This work is licensed under a Attribution-NonCommercial-ShareAlike 3.0 United States

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Avatar for Marcelo Mamud
5 years ago

Marcelo Mamud (Faculty)

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.