Table of contents Full Stack Deep Learning Course Content Setting up Machine Learning Projects Overview Lifecycle Prioritizing Archetypes Metrics Baselines 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 Overview Sources Labeling Storage Versioning Processing Machine Learning Teams Overview Roles Team Structure Managing Projects Hiring Training and Debugging Overview Start Simple Debug Evaluate Improve Tune Conclusion 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