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edX “Learning From Data” Caltech course


This introductory Machine Learning course taught by top Caltech professor Abu-Mostafa covers theory, algorithms and applications, with focus on real understanding. Starts Sep 25 on edX.



By Gregory Piatetsky, @kdnuggets, Sep 18, 2014.

Learning From Data Learning From Data, a top-rated Caltech course by a leading Caltech professor Yaser Abu-Mostafa, is an introductory course in machine learning (ML) that covers the basic theory, algorithms, and applications.

Course starts on edX on Sep 25, 2014 and will last 10 weeks.

About the course: ML is a key technology in Big Data, and in many financial, medical, commercial, and scientific applications. It enables computational systems to automatically learn how to perform a desired task based on information extracted from the data. ML has become one of the hottest fields of study today, taken up by undergraduate and graduate students from 15 different majors at Caltech. This course balances theory and practice, and covers the mathematical as well as the heuristic aspects. The lectures follow each other in a story-like fashion:
  • What is learning?
  • Can a machine learn?
  • How to do it?
  • How to do it well?
  • Take-home lessons.

 
The topics in the story line are covered by 18 lectures of about 60 minutes each plus Q&A.

MATLAB and LIONsolver are offering free licenses to all enrolled students for the duration of the course.

Register at

www.edx.org/course/caltechx/caltechx-cs1156x-learning-data-2516

The course lecture videos have been very popular with over 1.2 million hits on the videos on the Caltech Youtube and iTunes channels. In fact, the top 3 videos in all categories in the Caltech Youtube channel are 3 lectures from the course.

The most popular lecture videos from this course are:
  • Lecture 01 - The Learning Problem
  • Lecture 02 - Is Learning Feasible?
  • Lecture 10 - Neural Networks
  • Lecture 14 - Support Vector Machines
  • Lecture 03 -The Linear Model I
  • Lecture 04 - Error and Noise
  • Lecture 05 - Training Versus Testing

 
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