Hands-on ML engineering projects built while completing fast.ai Practical Deep Learning for Coders.
| Project | Type | Model | Dataset | Deployed |
|---|---|---|---|---|
| Guitar Classifier | Computer Vision | ResNet34 | Custom (Bing scraper) | HuggingFace Spaces |
| Titanic Survival Predictor | Tabular ML | tabular_learner | Kaggle Titanic | — |
| MNIST from scratch | Deep Learning fundamentals | Custom MLP | MNIST | — |
| SGD from scratch | Optimization | Manual PyTorch | — | — |
| NLP Sentiment (Lecture 4) | NLP | fine-tuned transformer | Custom CSV | — |
| California Housing | Regression | tabular_learner | sklearn dataset | — |
PyTorch · fast.ai · HuggingFace Transformers · Gradio · Jupyter · scikit-learn · Python 3.11 · uv
uv sync
source .venv/bin/activate
jupyter notebook- Lesson 1: Image classification, transfer learning
- Lesson 2: Deployment, Gradio, HuggingFace Spaces
- Lesson 3: SGD from scratch, ReLU, MNIST as tensors, tabular ML
- Lesson 4: NLP, fine-tuning transformers
- Lesson 5+: In progress