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Ask HN: Getting into Machine Learning?
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.
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'll really love it, and would be good at it.
Thanks for any ideas!
- PredictorY 8y agoSome 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.
- x0054 8y agoThanks 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!