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get good with linear algebra, probability, and statistics as well as calculus first. Then go for it.
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Andrew Ng's ML course on Coursera, and deeplearning.ai's (that's Ng again) deep learning specialization, also on Coursera. Best and most accessible introduction to both. Pay for the assignments and stuff, it worth it.
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Find a problem and solve it. ML is full of tutorials/courses on how to use Python libraries. Once people have finished them, the question is always, “OK. How do I use it to solve business problems?” Then they get pissed off that their company doesn’t do ML work.
ML seems to have become the latest library for Python devs to learn. “I know PyTorch. Time to apply for DS jobs.” -
Fast AI course is awesome if you want to get usable skills in a short period of time.
Its top down, so you learn theory after you've learned the practical stuff and that's often very helpful. -
If you want a support group, I’m trying to start something on Discord for proactive study and Kaggle sessions. It’s a constant cycle of learning so it’s good. Hmu with your Github if you’re interested.
I want to learn ML and DL at least at a good scale in 3 months. What should i do and how do i learn enough to create a basic projects ?
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