Full Stack Deep Learning
Full Stack Deep Learning
Full Stack Deep Learning
Course Content
Setting up Machine Learning Projects
Infrastructure and Tooling
Data Management
Machine Learning Teams
Training and Debugging
Overview
Start Simple
Debug
Evaluate
Improve
Tune
Conclusion
Testing and Deployment
Research Areas
Labs
Where to go next
Guest Lectures
Xavier Amatriain (Curai)
Chip Huyen (Snorkel)
Lukas Biewald (Weights & Biases)
Jeremy Howard (Fast.ai)
Richard Socher (Salesforce)
Raquel Urtasun (Uber ATG)
Yangqing Jia (Alibaba)
Andrej Karpathy (Tesla)
Jai Ranganathan (KeepTruckin)
Franziska Bell (Toyota Research)
Corporate Training and Certification
Corporate Training
Certification
Training and Debugging
How To Troubleshoot Your Deep Learning Models
We recommend a simple workflow for training and debugging neural networks.
As always, please
submit a pull request
if any information is out of date!
Slides
Videos
Overview
/course-content/training-and-debugging/overview
Start Simple
/course-content/training-and-debugging/start-simple
Debug
/course-content/training-and-debugging/debug
Evaluate
/course-content/training-and-debugging/evaluate
Improve
/course-content/training-and-debugging/improve
Tune
/course-content/training-and-debugging/tune
Conclusion
/course-content/training-and-debugging/conclusion
Previous
Hiring
Next
Overview
Last updated
8 months ago
Edit on GitHub
Contents
Slides
Videos
