Metadata-Version: 2.4
Name: modi_does_ml
Version: 0.1.0
Summary: ML Code Reference Library — sklearn and from-scratch templates
Home-page: https://github.com/yourusername/modi_does_ml
Author: Your Name
Author-email: your@email.com
License: MIT
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Requires-Dist: pandas
Requires-Dist: numpy
Requires-Dist: matplotlib
Requires-Dist: scikit-learn
Requires-Dist: seaborn
Dynamic: author
Dynamic: author-email
Dynamic: home-page
Dynamic: requires-python

# modi_does_ml — ML Code Reference Library

Ready-to-use Machine Learning algorithm templates,  
both **with sklearn** and **from scratch (no lib)**.

---

## Installation

```bash
pip install modi_does_ml
```

Or from source:

```bash
git clone https://github.com/yourusername/modi_does_ml
cd modi_does_ml_pkg
pip install .
```

---

## Quick Start

```python
from modi_does_ml import index

# Show all available modules
index.main()
```

---

## Generate a `.py` file

### Interactive (pick from numbered menu):
```python
from modi_does_ml import index
index.main()
```

### Direct (non-interactive):
```python
from modi_does_ml import index
index.generate('pca')
index.generate('k_means_clustering')
index.generate('lda_nolib')
```

---

## Available Modules

| Module Name               | Description                        |
|---------------------------|------------------------------------|
| `linear_regression`       | Linear Regression (sklearn)        |
| `logistic_regression`     | Logistic Regression (sklearn)      |
| `decision_tree`           | Decision Tree (sklearn)            |
| `random_forest`           | Random Forest (sklearn)            |
| `svm_lineardata`          | SVM Linear Kernel (sklearn)        |
| `svm_nonlineardata`       | SVM RBF Kernel (sklearn)           |
| `k_means_clustering`      | K-Means Clustering (sklearn)       |
| `pca`                     | PCA (sklearn)                      |
| `svd`                     | SVD (sklearn)                      |
| `lda`                     | LDA (sklearn)                      |
| `xgboost`                 | XGBoost (sklearn)                  |
| `linear_regression_nolib` | Linear Regression (from scratch)   |
| `logistic_regression_nolib`| Logistic Regression (from scratch)|
| `decision_tree_nolib`     | Decision Tree (from scratch)       |
| `random_forest_nolib`     | Random Forest (from scratch)       |
| `svm_lineardata_nolib`    | SVM Linear (from scratch)          |
| `svm_nonlineardata_nolib` | SVM RBF (from scratch)             |
| `k_means_clustering_nolib`| K-Means (from scratch)             |
| `pca_nolib`               | PCA (from scratch)                 |
| `svd_nolib`               | SVD (from scratch)                 |
| `lda_nolib`               | LDA (from scratch)                 |
| `xgboost_nolib`           | XGBoost / Boosting (from scratch)  |

---

## License

MIT
