Hey guys, I'm a CS student in college looking to supplement my education with some big-name buzzword topics. Namely deep learning. I get the idea, but I wanted to take an online course or two to actually teach me the implementation process. I was wondering if anyone has any suggestions other than the Jason C courses on udemy (he splits deep learning up into many lessons and every single one is $35... ) or the UToronto course on coursera. Or experience with those two that will make me want to take them. As a broader question, in general, what are some good online course providers for programming and mathematics subjects?

Ever wanted to program VSTs? Here's ablog I found awhile ago. Very informative, with supplemental coding and builds: Making Audio Plugins - Martin Finke's Blog

Have you considered looking at resources from Big Data University or other statistical/data analytics sites? The statistical side of machine learning is easier to delve into (as it tends to be applied) than the pure mathematics of the theory behind machine learning, unless of course you're comfortable with real analysis. MIT Open Courseware isn't bad either: Mathematics of Machine Learning | Mathematics | MIT OpenCourseWare

My friend Rebecca (who wrote Wekinator), just did a MOOC that's a very gentle introduction to ML (more for artists and non-technical people): https://www.kadenze.com/courses/machine-learning-for-musicians-and-artists/info Enrollment is closed at the moment though. Here's a free online book that goes into deep learning that looks pretty good: Neural networks and deep learning AFAIK, Norvig's PAIP is still *the* classic AI text: Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp: Peter Norvig: 9781558601918: Amazon.com: Books There are probably more modern, targeted books that people recommend now, but that goes deep on all the underlying theory. Plus, Lisp.

I'm not sure if I'm looking for a textbook to get through, as I tend to not be able to finish textbooks without instruction. I'll look into it though. I'm also not that familiar with Lisp. Never heard of it before. Checking it out now. I didn't before, in fact I was just looking for AI courses, but...now I'm interested. I don't know a lot of Stat stuff, but I am actually really familiar with real analysis and theory. I'm in a CS school where we get really into theory of computation and whatnot. I am looking for a course more in the implementation than the theory, though. I'll look at Big Data University, but I must say there name doesn't sound all that enticing. Kind of buzzword-y. Looking at the MIT page now...

Weka 3 - Data Mining with Open Source Machine Learning Software in Java You can play with it and try to check out the algorithms that are implemented.

I don't know much about BDU other than it was recommended for a light introduction to HADOOP for free in my data mining course. I gave it a go, but felt it wasn't quite what I was looking for in a course. That might just be my expectations though. I've had some experience in working with ANN, Decision Trees, Random Forests, k-Means (and other clustering methods, basic text-mining and a few other techniques from an applied statistical POV. I would like to get into the theory-side a bit more, but haven't taken the plunge into self-learning RA yet.

If you are into OS level stuff and Linux specifically buy some oreilly books on the kernel and try your hand at the eudyptula challenge. I don't know if this is really along the lines of your interests but it is fun if you see yourself going more low level. The Eudyptula Challenge

These are directly from a recent Reddit post I saved Source: https://www.reddit.com/r/AskReddit/comments/4q91g9/what_free_things_online_should_everyone_take/