- Notes of Lesson 3 and 4

  • inference • probability • stanford • ai • notes • three • four • course • 3 • peter norvig • 4 • online • monty hall • lesson • bayes network • class • sebastian thrun
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This week the ai-class was about Probability, Bayes Networks and Inference.

For people like me, that have to find patches of free time to study this course, there is a good news: you can do Homeworks 2 just by studying the first of the 2 lessons. This can help to prioritise your schedule, and study the second lesson (that focuses on the “computation” over Bayes Networks) with a little bit more peace of mind.

Sherlock Holmes This guy was great at inference ;-)

Of course, I’m assuming you are doing the Advanced Track, where there are deadlines.

I have here my notes of the 2 classes:

The second notes about “Inference” are still a work in progress, as I completed only half of the videos so far. Will try to finish it before Monday.

Now it’s time for some mussles.

UPDATE 1: I have been asked for the notes of my Homework 1. Here you go. But bear in mind: given those are homework, I didn’t put in them proper explanation. I suggest you watch the videos for that. ;-)

UPDATE 2: I’m done with notes of Lesson 4, “Probabilistic Inference”. Prof. Norvig concludes the lesson presenting the Monty Hall Problem: a very interesting one! If you want my explanation of the Monty Hall problem, check out my notes. I think I did a decent job at explaining it.