Machine Learning Must-Reads: Fall Edition

Getting a handle on the current state of machine learning is tricky: on the one hand, it takes time to catch up with foundational concepts and methods, even if you’ve worked in the field for a while. On the other hand, new tools and models keep popping up at a rapid clip. What’s an ML learner to do?

We tend to favor a balanced, cumulative approach—one that recognizes that no single person can master all the knowledge out there, but …

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