Top 13 Deep Learning Tips and Tricks

  1. Understand model complexity
    • how does data affect model: complexity depends only on the first layer size
  2. Establish a baseline on holdout data: try different algos/ models and check
  3. Inspect model in flow
  4. Use early stopping for deep learning! Use a validation set
  5. Control scoring overhead: a smaller validation dataset and sample it, even score less
  6. Use N-fold CV: get directly the optimal training time with early stopping
  7. Perform hyper-parameter search: you just need to find one of the good models
  8. Use checkpointing: save your model in your disk when need!
  9. Tune communication on multi-node
  10. Know your data
  11. Advanced math in proba
  12. Do ensembling: vote or just weight!
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