Neural Network Debugging Guide
Guide users through systematic neural network debugging with this AI prompt, focusing on diagnosing issues and improving model performance.
What this prompt does
- Guides users through a systematic model improvement process based on Andrej Karpathy's debugging approach.
- Focuses on diagnosing issues through data inspection, simplification experiments, and regularization adjustments.
- Adapts the approach based on user's model performance gaps, complexity of issues, experience level, and available resources.
How to use this prompt
- Run the full prompt and answer the questions as detailed as possible.
- Example: "My model is trying to classify images of cats and dogs. The accuracy is 70%, but I expected at least 90%. The loss curve is erratic, and validation accuracy is plateauing. I've tried adjusting the learning rate and adding dropout, but it didn't help. I can dedicate 10 hours a week and h…
Premium prompt — included in the Complete AI Bundle. Part of the Coding prompts collection in the God of Prompt library.