Full Stack Deep Learning
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Full Stack Deep Learning
Course Content
Setting up Machine Learning Projects
Infrastructure and Tooling
Overview
Software Engineering
Computing and GPUs
Resource Management
Frameworks and Distributed Training
Experiment Management
Hyperparameter Tuning
All-in-one Solutions
Data Management
Machine Learning Teams
Training and Debugging
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
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GitBook
Infrastructure and Tooling
The Training and Evaluation Phases of Your Machine Learning Workflow
The infrastructure landscape of deep learning.
As always, please
submit a pull request
if any information is out of date!
Slides
Slides for the entire module. Go to the next page for the first video!
Videos
Overview
Software Engineering
Computing and GPUs
Experiment Management
Hyperparameter Tuning
All-in-one Solutions
Previous
Baselines
Next
Overview
Last modified
2yr ago