Pocket Guide

A Practical Guide to Deep Learning: From Data to Deployment

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Use this pocket guide to quickly explore how to prepare data and create deep learning models that run efficiently in production.

Practical Deep Learning:
Key Takeaways

  • Use deep learning to find complex patterns across large solution spaces.

  • Training a network with deep learning requires a lot of quality labeled data.

  • Good data preparation can significantly increase the deep learning model’s accuracy.

  • Instead of creating a network from scratch, perform transfer learning on a pretrained model.

  • Before deployment, test that the model interacts as expected with the other system components.

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