Distribution Shift — Topic Summaries
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Lecture 7: Troubleshooting Deep Neural Networks (Full Stack Deep Learning - Spring 2021)
Troubleshooting deep neural networks is hard because the same drop in performance can come from many different causes—and many bugs don’t announce...
Evaluate (4) - Troubleshooting - Full Stack Deep Learning
Model improvement starts with evaluation, not guesswork: once a team is reasonably confident the model is bug-free, the next move is to measure...
Improve (5) - Troubleshooting - Full Stack Deep Learning
Model improvement starts with a simple priority order: fix underfitting first, then tackle overfitting, and only after both training and validation...