Troubleshooting Deep Neural Networks - Full Stack Deep Learning - Spring 2021

Learn a step-by-step strategy to debug neural networks in this comprehensive lecture from the Full Stack Deep Learning Spring 2021 series. Explore why deep learning troubleshooting is challenging and discover a decision tree approach to tackle issues. Begin with simple implementations, master debugging techniques, and learn how to evaluate your models effectively. Delve into methods for improving both models and data, and gain insights on tuning hyperparameters to optimize performance. Follow along as the lecture covers key topics including the complexities of deep learning troubleshooting, implementation strategies, evaluation techniques, and advanced optimization methods over the course of 1 hour and 7 minutes.

- Introduction
- Why Is Deep Learning Troubleshooting Hard?
- Decision Tree For Deep Learning Troubleshooting
- Start Simple
- Implement and Debug
- Evaluate
- Improve Model and Data
- Tune Hyperparameters