Full Stack Deep Learning

What do we cover?

  • Formulating the problem and estimating project cost
  • Finding, cleaning, labeling, and augmenting data 
  • Picking the right framework and compute infrastructure
  • Troubleshooting training and ensuring reproducibility
  • Deploying the model at scale

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