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by muninn_
3465 days ago
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Seems interesting. I haven't been able to look through all of the links, but I assume there are practical exercises and "homework"? When people say "I don't do or have the opportunity to do ML at work" it's because they don't have data to analyze or actual things to program or do in order to gain the experience they need to make the videos worthwhile to watch. If I were to watch 10 videos on ML, but not actually go write code or analyze data, then the videos aren't going to get me a ML job or be that helpful other than learning a little about the topic. It's kind of like watching a open course on ancient history or some similar topic, but without writing a paper on it. Yes the video is interesting, but what gets me a job and experience is the thought and work that goes into the homework. But even if these were just videos, it's a good resource. |
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One thought about that: If you don't have "work data" to work on, there's still TONS of other "stuff" out there that you can work with. And given how much Open Data / Linked Data datasets are out there, for many industries I'd bet there's a pretty good chance one could find some interesting analysis of one of those datasets that would have value for their employer. Digging in and building something like that could help with bridging into an ML role. Or, if it's obvious that it just Isn't Going To Happen with one's current employer, it's always possible to just build something cool around an Open Data dataset and plop it up on GitHub to show other people. And in either case, it provides the motivation of having a project to work on.
There are also Kaggle competitions.