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> but if you ask them why something works (or why a variation may not work) Interesting. Do you have an example? Is it common for people to practice ML problem

• mudrockbestgirl 4y ago
  It's the opposite of leetcode because it tests understanding, not memorization. For example, you could ask why position embeddings are necessary and what would happen without, reasoning behind certain terms in an objective function and what would happen without them, which part of an architecture the bottleneck for convergence is, intuitively what tuning a certain hyperparameter does, show them a timeseries of gradients for something that doesn't convergence and ask what's wrong with them, etc. I'm just making these up because the questions we previously asked were domain-specific to our applications, e.g. "why is this specific learning objective hard" or "what would you modify to help generalization in case X" These questions are very easy to talk about for someone with a strong ML background. They may not always know the answer and often there is no right answer, but they can make reasonable guesses and have a thought process around it. Someone who just took a MOOC likely has no idea how to even approach the question.