12.7 Full Stack Deep Learning


Since 2012, deep learning has lead to remarkable progress across a variety of challenging computing tasks, from image recognition to speech recognition, robotics, and audio synthesis. Deep learning has the potential to enable a new set of previously infeasible technologies like autonomous vehicles, real-time translation, and voice assistants and help reinvent existing software categories. There are many great courses to learn how to train deep neural networks. However, training the model is just one part of shipping a deep learning project. This course teaches full-stack production deep learning:

  • 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