Peter Norvig is really an impressive teacher.

I have been doing his course "Design of computer programs" (https://www.udacity.com/course/cs212) and it really push me from basic/novice developer to intermediary.

He succeed to explain you things in a natural way. He seems to always start by the basic assumption. Working and thinking around any problems/surprises he/you encounter. So, you have the impression to discover things more than learning them.

I frequently and Highly recommend "Design of computer programs" to everyone I can. As an intermediate developer before taking it, I still recommend it. He is an amazing teacher I have learned considerably just from the way he explains and approaches problems.

Plus taking a class for free from the director of research at google :)

Google Schmoogle - Peter Norvig is a powerhouse name and Google gains in prestige for having Peter Norvig, not the other way around.

I didn't realize he taught any udacity courses, thanks for the link!

Interesting...being the winner of a programming contest was a negative factor when they evaluated later performance at Google.

@1:11:50

Thanks... Was just about to send out an application today that mentions me quickly winning a contest. Probably there's lots of dumb stuff I'm putting on my applications that I think makes me look good, but is seen as very bad. Wish I had someone who knows these secret factors to run my applications by.

Makes me kind of upset that many employers and investors keep some of their favorite indicators totally secret, except for a few insiders that they share them with.

Unfortunately Google hasn't hired a million programmers yet so perhaps their ML algorithms aren't good yet at knowing what actually makes people good. In fact, I think it is actually rather fool-hardy when I hear people talking about analyzing resumes to predict candidates, or other such nonsense.

Just interview some people. Don't ask crazy algorithm questions either, watch the person do what they are suppose to do. It worked great while I was at Pivotal Labs. We would sit down with engineers and pair program with them for a while. It became rapidly clear whether or not they were good, mostly because we were evaluating them on the exact criteria for which we were searching.

What was the book he recommends at the beginning? It is hard to make out. Also can anybody recommend their resources for machine learning or AI in general?

http://aima.cs.berkeley.edu/ is the book being held up by the fellow introducing him. (That page also has a collection of links to resources; not sure how up-to-date.)

It really starts at around 00:11:00