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I highly recommend https://course.fast.ai/ . It's much more top down: in the first lesson or two, you train a NN image classifier, rather than starting with first principles and linear algebra. I found this structure to be more motivating and effective.
I went through both, but I definitely think fastai is the better starting point.
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What are the others? Any recommendations?
I took these courses from Georgia Tech via OMSCS but they are also on udacity. https://omscs.gatech.edu/cs-7641-machine-learning https://omscs.gatech.edu/cs-7642-reinforcement-learning (I took this before ML but its supposed to come after. There is some overlap. Probably my favorite graduate course.) https://omscs.gatech.edu/cs-7646-machine-learning-trading (IMO not amazing) Much more basic (took this before OMSCS):…
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They say you can "audit" the course for free, but they employ a ton of grey patterns to get you to pay for it. I haven't been able to find out where to audit it yet. Update: You have to go into the individual courses within the specialization and the enroll popup will have an audit option. First Course is here: https://www.coursera.org/learn/neural-networks-deep-learning...
IIRC you need to pay if you want your assignments to be (auto-)graded.
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OTOH, the time I spent learning Octave/Matlab for Andrew Ng's course was 100% wasted time, because I've never used it again in the 10+ years since I took the class, whereas time spent learning Python would've been useful to me in myriad other ways.
So sad to hear Mariah disparaged. I’m an Gen X engineer and Matlab is one of our first languages. Use it today still in aerospace but I would imagine Python suits software shops much better. Does Python handle matrix math as well?
If you're playing around interactively, it's a bit easier to write (in Matlab)
m = [1 0 0 ; 0 0 -1 ; 0 1 0]
m = np.array([[1, 0, 0], [0, 0, -1], [0, 1, 0]])
m = rand(3,4)
a = [0.1 0.2 0.3]
m \ a'
m = np.random.rand(3,4)
a = np.array([0.1, 0.2, 0.3])
np.linalg.lstsq(m, a.T)
wtf?
google...
fine!
a = np.array([[0.1, 0.2, 0.3]])
np.linalg.lstsq(m, a.T)
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I went through both, but I definitely think fastai is the better starting point.
Can you say more?
When I was younger and didn't work full time + have other commitments the bottoms up approach appealed to me more, I think partially because I had bigger time blocks to allocate. i.e I could spend a whole weekend just learning fundamentals of some particular thing I was interested in and reach the first levels of usefulness in that one "session".
These days smaller time blocks mean that I need to walk away with something the keep the spark going for most curiosities.
Although this is the best course on ML, is it really practical for anything? Has anyone built products for things they’ve learned from this course?
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Can you say more?
I didn't do these particular courses but I found it a lot easier to stay motivated with the top down approach. First demonstrate usefulness, then deepen fundamentals. When I was younger and didn't work full time + have other commitments the bottoms up approach appealed to me more, I think partially because I had bigger time blocks to allocate. i.e I could spend a whole weekend just learning fundamentals of some parti…
I second this - while both are great courses, I found I could only dedicate very short amounts of time recently to any kind of study, and going from the ground-up more thoroughly seemed like I was making no progress. The fast.ai top down approach worked a bit better for me for those reasons, otherwise it would have been interesting starting with the deep dive.
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I'll ask the opposite question.. how much do these courses cost? Some quick googling has led me to Coursera, but their pricing model seems a bit obtuse. So if they're going to try and grey-pattern me into paying i'm trying to understand how much i would pay. I don't care about a degree from these places, i'd just like to learn. (specifically the crypto course sounds interesting)
You can also purchase an yearly Coursera subscription for $299 or $399 and get access to all the specializations/projects on Coursera for one year.
https://www.coursera.support/s/article/360036151932-Courses-...
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I went through both, but I definitely think fastai is the better starting point.
Can you say more?
Similarly, when I learned web development with Rails over a decade ago, I didn't start by building an HTTP stack. I started by doing the build-a-blog-in-fifteen-minutes tutorial. Now I had a working project. Eventually I needed to learn all of the underlying technologies, but it's much easier and more rewarding to have something running first.