28 lines
1.4 KiB
Markdown
28 lines
1.4 KiB
Markdown
📖 **Full write-ups with result plots:** [docs/Home.md](docs/Home.md)
|
|
# Machine Learning Portfolio
|
|
A collection of end-to-end machine learning projects covering regression, classification, and linear models built from first principles.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
## Projects
|
|
|
|
| Project | Task | Highlight |
|
|
|---|---|---|
|
|
| [housing-price-regression](housing-price-regression/) | Regression | Full pipeline (EDA → feature engineering → tuning → evaluation), test R² 0.72 |
|
|
| [classification-project](classification-project/) | Classification | Binary/multiclass/multilabel/multioutput on MNIST, Random Forest ROC AUC 0.997 |
|
|
| [linear-models](linear-models/) | Linear models | Normal equation, gradient descent, and regularization implemented from scratch |
|
|
|
|
Each project folder has its own README with the specific approach, results, and notebook.
|
|
|
|
## Tech stack
|
|
|
|
Python, pandas, NumPy, scikit-learn, matplotlib, seaborn
|
|
|
|
## Author
|
|
|
|
**Reza** — Computer Networks student, LPIC-1
|
|
[GitHub](https://github.com/rezayaghobi-dev)
|
|
s |