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[D] Chances on getting into a ML PhD without engineering background

Hi, I have a unusual background and I am looking at getting into a PhD in machine learning. Do you think it is possible to get into a ML PhD without an engineering background? I studied business in my bachelor in Europe, and since it had a relatively decent amount of math I got into a master specialising in financial engineering. The master was particularly quantitative. I am now working as a trader, doing a mix of quant/non-quant trading. And some of it is ML-based. For the last 2 years I really got into ML, taking classes on my free time (Learning from Data, reading Deep Learning book and other ML books, and now the David Silver RL class). And I found it so interesting that I want to spend more time on it and do research. Given how competitive PhD applications are, do I stand any chances, since my background is not pure engineering? If yes, any advices on how to start?

Note: While I am interested in many applications, I would be interested to research RL in trading too and I guess my profile would fit nicely there. But unfortunately it is not a developed area of research so it is difficult to point myself in that direction during applications.

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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.