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I'm currently pursuing an undergrad in Computer Science and Engineering from an Indian university. I really like machine learning, but of late, I've been doing some digging and I think I really like quantum algorithms. So I thought it'd be for the best if I could intersect the two subjects: This is how I stumbled upon Quantum Machine Learning. But the problem is, I noticed that most of the contributors in this field are from a physics background, which I found very discouraging.

Is there any way I can study quantum learning models and related stuff, keeping in mind my current background? I'll be applying for my GRE's and making applications (most probably for a PhD) by the end of next year. What are some of the courses that I should look out for?

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    My impression is that you can understand quantum computing without knowing much about physics. What you really need, I think, is linear algebra. You might try reading Quantum Computing Since Democritus by Scott Aaronson. You could also check out Q is for Quantum, a short book that attempts to explain quantum computing for people with very little math background, but also without watering down the ideas.
    – littleO
    Nov 18, 2019 at 6:02
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    I feel it's actually easier to get into quantum computing with a CS background than with a physics background, at least if you want to do algorithmics Nov 18, 2019 at 7:51
  • Thanks for the optimistic comments. I checked out the books as recommended to me by @littleO and they were great! On a note here, I really like the math behind Quantum Computing and I'd prefer not to shy away from the gritty mathematical ideas :) Nov 18, 2019 at 11:58

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