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If you want a great introduction, check out Andrew Ng's Coursera course: https://www.coursera.org/learn/machine-learning https://www.coursera.org/learn/machine
by cr0sh 8y ago
If you want a great introduction, check out Andrew Ng's Coursera course:
https://www.coursera.org/learn/machine-learning https://www.coursera.org/learn/machine-learning
This is the same course that was originally called "ML Class" in 2011 when it was offered via Stanford (it, plus the other course called "AI Class" - helped to launch Coursera and Udacity, respectively). It uses Octave as it's development language to teach the concepts.
Octave has as it's "primitives" the concept of the Vector and Matrix; that is, it is a language designed around the concepts of linear algebra. So, you can easily set a variable to the values that make up a vector, set another to say the identity matrix, multiply them together, and it will return a matrix.
But the course is initially taught showing how to do all of this "by hand" (much like this tutorial) - using for-next loops and such; essentially rolling your own matrix calcs. Then, once you know that, you are introduced into how to use the built-in calcs provided by octave, etc.
It is really a great course, and I encourage you to try it. It opened my eyes and mind to a lot of concepts I had been trying to grasp for a while that just didn't click until I took that course in 2011.
Of course, once it did, I was like "that's it? why couldn't I see that?" - such is the nature of learning I guess!
His method of building up from the basics all the way to a neural network using Octave will be a good foundation for further learning or playing with other tools like TensorFlow; I ended up taking a couple of other later MOOCs offered by Udacity (focused mainly on self-driving vehicle concepts), and ML Class (and what I took of AI Class) really helped to prepare me.
It also showed me things I was deficient in (something I need to correct some day). But that's a different story.
Suffice to say, that course will "unveil the magic"; it was really an amazing course that I am glad I took. Oh - and to show you what you can do with what you learn in that course, a fellow student during that time ended up making this (and the course was not even finished when he did it):
https://blog.davidsingleton.org/nnrccar/ https://blog.davidsingleton.org/nnrccar/
Throughout the course, the ALVINN autonomous vehicle was referenced quite often, and it inspired him to recreate it successfully in miniature. It also serves to show just how far computer technology has come - what used to take a van-load of equipment can now be played around with using a device that fits in your pocket!
- avmich 8y agoThis is a great course, I took it once a few years ago and sometime think if I should take it again. Wonder how it changed over time. It was eye-opening training a small NN by hand on MNIST dataset and getting it to recognize digits surprisingly well. However even understanding all that doesn't allow one using modern frameworks by itself, they seem to carry too much additional assumptions, terminology which aren't quite explained with similar level of patience.