Top Highlights

• Consider spending a few hours a week on an online course. We recommend either of these two: The fast.ai online course, “Practical Deep Learning For Coders, Part 1” Google’s ML Crash Course
• You should strongly consider contacting the teams you’re interested in at this stage. Send them an email with the specifics of what you’re planning on spending your time on to get feedback on it. The manager of the team may suggest specific resources to use, and can help you avoid wasting time on extraneous skills you don’t need for the role.
• The most straightforward way to gain this experience is to choose a subfield of ML relevant to a lab you’re interested in. Then read a few dozen of the subfield’s key papers, and reimplement a few of the foundational algorithms that the papers are based on or reference most frequently. Potential sub-fields include the following: Deep reinforcement...
• Daniel and his housemate used Josh Achiam’s Key Papers in Deep RL list to guide their efforts. They got through about 20-30 of those papers, spending maybe 1.5 hours independently reading and half an hour discussing each paper. More importantly, they implemented a handful of the key algorithms in TensorFlow: Q-learning: DQN and some of its extens...

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