Full Stack Deep Learning
Search
⌃
K
Full Stack Deep Learning
Course Content
Setting up Machine Learning Projects
Infrastructure and Tooling
Data Management
Machine Learning Teams
Training and Debugging
Testing and Deployment
Project Structure
ML Test Score
CI / Testing
Docker
Web Deployment
Monitoring
Hardware/Mobile
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
Powered By
GitBook
Testing and Deployment
The Testing and Deployment Phase of Your Machine Learning Workflow
It's useful to break down the different systems and tests necessary for a successful ML project.
As always, please
submit a pull request
if any information is out of date!
Slides
Videos
Project Structure
ML Test Score
CI / Testing
Docker
Web Deployment
Monitoring
Hardware/Mobile
Previous
Conclusion
Next
Project Structure
Last modified
3yr ago
