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 Kaggle.com
- 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”