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Get Start on Machine Learning

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So here comes 2017, a year when you hear people talk about the words Machine Learning, Reinforcement Learning, and Artificial Intelligence everywhere.

Last year when Mark Zuckberg was working on building Jarvis, I didn’t spend much time on AI or Machine Learning. But I know the efforts I made last year get me ready to start on it right now.

Tonight I just talked to a former colleague who is working at Nvidia, and he gave me a few helpful suggestions about getting started on machine learning according to his own experience. Here are some of his advices:

  • Set a goal: What do you want to achieve with the knowledge of Machine Learning?
  • Learn the fundamentals: Andrew Ng’s course on Coursera
  • If you’d like to have more courses, take Standford CS231n
  • Learn to use the frameworks: Tensor Flow, Caffe
  • Work on projects with real data (very important): get from
  • Follow OpenAI and DeepMind
  • Master Python if you haven’t
  • Make sure your computer has a powerful GPU :)

Some people I know might think Machine Learning or AI is sort of irrelevant to what I’m working on. That’s not what I think though. Even if it is irrelevant today, it will become relevant sooner than expected. Machine Learning is not a fad. It’s the way how technology works tomorrow. If you can’t master it, at least you need have a good understanding of it.

Image source: Medium “20 things I’ve learned from Larry Page”