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Lecture 09: Ethics (FSDL 2022)
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Classroom Contents
Full Stack Deep Learning - 2022
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- 1 Lecture 01: When to Use ML and Course Vision (FSDL 2022)
- 2 Lab Intro and Overview (FSDL 2022)
- 3 Lab 01: Neural networks in PyTorch (FSDL 2022)
- 4 Lab 02: PyTorch Lightning and Convolutional NNs (FSDL 2022)
- 5 Lab 03: Transformers and Paragraphs (FSDL 2022)
- 6 Lecture 02: Development Infrastructure & Tooling (FSDL 2022)
- 7 Lab 04: Experiment Management (FSDL 2022)
- 8 Lecture 03: Troubleshooting & Testing (FSDL 2022)
- 9 Lab 05: Troubleshooting & Testing (FSDL 2022)
- 10 Lecture 04: Data Management (FSDL 2022)
- 11 Lab 06: Data Annotation (FSDL 2022)
- 12 Lecture 05: Deployment (FSDL 2022)
- 13 Lab 07: Web Deployment (FSDL 2022)
- 14 Lecture 06: Continual Learning (FSDL 2022)
- 15 Lab 08: Monitoring (FSDL 2022)
- 16 Lecture 07: Foundation Models (FSDL 2022)
- 17 Lecture 08: ML Teams and Project Management (FSDL 2022)
- 18 Lecture 09: Ethics (FSDL 2022)
