AI tools like ChatGPT and GitHub Copilot are more than novelties—they're game-changers for ML devs. When used right, they help you debug faster, write cleaner code, and build with more confidence.
🛠 Use ChatGPT to Scaffold Code
- “Write a PyTorch classifier for MNIST dataset with training loop.”
- “Generate a function to evaluate model with precision and recall.”
- “Explain this TensorFlow error and suggest a fix.”
🧹 Refactor and Clean Code Automatically
- Paste your messy code and ask for optimization suggestions
- Request docstrings or code comments in-line
- Ask for test case generation
🔄 Speed Up Debugging
- Describe the issue and share the traceback with GPT
- Use GPT to simulate unit test responses or error analysis
- Validate edge cases and get second-opinion logic checks
💡 Bonus: Prompt Engineering for ML Tasks
- “Compare Gradient Boosting vs Random Forest for tabular data.”
- “What’s a good CNN architecture for image classification under 10k samples?”
- “Summarize pros/cons of XGBoost vs LightGBM.”
Smart devs use smart tools. Let AI help you write AI—just be sure you verify and test everything rigorously.
