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Deep Learning Checklist
- Define the problem
- Identify a way to reliably measure success against a goal
- Prepare a validation process that you will use to evaluate models
- Vectorize the data
- Develop a model that beats a trivial common sense baseline
- Refine model architecture
- Get your model to overfit
After overfitting use the following to refine model architecture
- Add regularization (dropout) to the model
- Downsize the model to use lower capacity