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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 pretender
by PredictorY 8y ago
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.
- 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!