Metadata-Version: 2.4
Name: linreg-douaa
Version: 1.0.0
Summary: Simple linear regression from scratch (gradient descent)
Home-page: https://pypi.org/project/linreg-douaa/
Author: Khoualed Douaa
Author-email: your.email@example.com
License: MIT
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE.txt
Requires-Dist: numpy
Dynamic: author
Dynamic: author-email
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: license
Dynamic: license-file
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

# linreg-douaa

A tiny simple linear regression model (`y = m*x + b`) written from scratch
with NumPy and trained with gradient descent.

## Install

```bash
pip install linreg-douaa
```

## Usage

```python
import numpy as np
from linreg import LinearRegression

x = np.array([1, 2, 3, 4, 5], dtype=float)
y = 2 * x + 1

model = LinearRegression(lr=0.01, epochs=5000)
model.fit(x, y)

print(model.m, model.b)       # ~2.0, ~1.0
print(model.predict([6, 7]))  # ~[13, 15]
print(model.r2_score(x, y))   # ~1.0
```

Note: the install name is `linreg-douaa`, the import name is `linreg`.

## License

MIT
