“I am a student of computer science/engineering. How do I get into the field of machine learning/deep learning/AI?”
It’s never been easier to get started with machine learning. In addition to structured MOOCs, there is also a huge number of incredible, free resources available around the web.
Here are just a few that have helped me:
- Start with some cool videos on YouTube. Read a couple of good books or articles. For example, have you read “The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World”? And I can guarantee you’ll fall in love with this cool interactive page about machine learning?
- Learn to clearly differentiate between buzzwords first — machine learning, artificial intelligence, deep learning, data science, computer vision, robotics. Read or listen to the talks, given by experts, on each of them. Watch this amazing video by Brandon Rohrer, an influential data scientist. Or this video about the clear definition and difference of various roles associated with data science.
- Have your goal clearly set for what you want to learn. And then, go and take that Coursera course. Or take the other one from Univ. of Washington, which is pretty good too.
- 1. Follow some good blogs: KDnuggets, Mark Meloon’s blog about data science career, Brandon Rohrer’s blog, Open AI’s blog about their research, and of course, Heartbeat
- If you are enthusiastic about taking online MOOCs, check out this article for guidance.
- Most of all, develop a feel for it. Join some good social forums, but resist the temptation to latch onto sensationalized headlines and news bytes posted. Do your own reading, understand what it is and what it is not, where it might go, and what possibilities it can open up. Then sit back and think about how you can apply machine learning or imbue data science principles into your daily work. Build a simple regression model to predict the cost of your next lunch or download your…
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