The following notes represent a complete, stand alone interpretation of Stanford's machine learning course presented by Professor Andrew Ng and originally posted on the ml-class.org The topics covered are shown below, although for a more detailed summary see lecture 19. The only content not covered here is the Octave/MATLAB programming. All diagrams are directly taken from the lectures, full credit to Professor Ng for a truly exceptional lecture course. To access this material, follow this link.

Together they contribute 30% to your overall course mark. Both assignments are to be submitted using the submit command on DICE. You should put all of your work into one prolog file (commenting out any written sections) and submit the file before the deadline. Details of how to use the submit command will be provided at the end of each assignment. Both assignments require you to develop complete Prolog programs. You may develop these programs at home on a PC or Mac but you must test that they run under the DICE version of sicstus before submission.

The Educational Advances in Artificial Intelligence column discusses and shares innovative educational approaches that teach or leverage AI and its many subfields at all levels of education (K-12, undergraduate, and graduate levels). I credit these positive changes to the active in-class learning and a new enthusiasm for teaching, as well as the first-rate lectures by Stanford professors Jennifer Wisdom and Andrew Ng. I was showed that students liked this SPOC format, although pleased when students, enrolled in Introduction to there were suggestions for better in-class and Artificial Intelligence Class MOOC CS188x at the MOOC-content coordination. Had I tweaked my University of California, Berkeley, came to my channel course and continued along this path, I might have for remediation, taking word back to the MOOC's achieved phenominal success, but sadly I left the discussion forum. I required students in my graduate SPOC format behind.

Column n The Educational Advances in Artificial Intelligence column discusses and shares innovative educational approaches that teach or leverage AI and its many subfields at all levels of education (K-12, undergraduate, and graduate levels). In this column I describe my experience adapting the content and infrastructure from massive, open, online courses (MOOCs) to enhance my courses in the Department of Electrical Engineering and Computer Science at Vanderbilt University. I begin with my informal, early use of MOOC content and then move to two deliberatively designed strategies for adapting MOOCs to campus (that is, wrappers and small private online classes [SPOCs]). I describe student reactions and touch on selected policy and institutional considerations. In the never-ending search for increasing student bang-for-the-buck, I was motivated to increase the bang, rather than reduce the buck, the latter being well above my pay grade.

The final semester starts this week! As usual, the live lectures will be on Twitch on Fridays at 18:00 MSK, and the recorded videos will be on Youtube.