
Ask HN: Getting into Machine Learning? - x0054
Recently I took a Coursera course by Andrew Ng on Machine Learning, and I have to say, I absolutely love this subject. Somehow it just clicks in my brain. I vectorized backpropagation early on, even though in the course Andrew tells you not to try at first, and the speed improvement was a marvel to behold.<p>So, to sum up, I really love the subject and want to learn a lot more! But I also need to eat ;) and I learn way better while doing. My background is in law and finance, though I do have coding skills in Swift, JS, PHP and Python, but nothing significant. Any recommendations for getting into the ML field without official CS degree or something similar? I think I&#x27;ll really love it, and would be good at it.<p>Thanks for any ideas!
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PredictorY
Some general suggestions:

\- At least occasionally read something that isn't on a screen (in a book).

\- Do some experimentation on your own. Too many pretenders in this field
parrot whatever they heard elsewhere. It's hard to argue with actual results.

\- Don't mindlessly chase whatever's trendy: that's an endless treadmill and
"the crowd" wastes a lot of time.

\- Once you understand a few machine learning algorithms, you probably have
enough. A bigger toolbox is better, but I recommend paying attention to things
other than the machine learning activity itself, such as application of
machine learning to the problem, data collection, data preparation and model
validation.

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x0054
Thanks for the advice! Yes, reading in any field is paramount. Not sure about
the screen limitation, since most of my library is on my laptop as is, but I
get the point. :) And I know what you mean about actually experimenting with
the tools for yourself and not chasing the latest thing. I am not getting into
ML for the money, I would keep doing what I am doing now if that was the goal.
I really do find it interesting and fascinating. I always loved math, but
never really found an interesting application for it until stumbling on this
subject while doing research into Micron, of all things.

Anyway, thanks again!

