Metadata-Version: 2.4
Name: aek-auto-mlbuilder
Version: 0.3.2
Summary: Automatic ML model builder in Python
Home-page: https://github.com/alpemre8/aek-auto-mlbuilder
Author: Alp Emre Karaahmet
Author-email: alpemrekaraahmet@gmail.com
License: MIT
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: scikit-learn>=1.0
Requires-Dist: numpy>=1.23
Requires-Dist: pandas>=1.5
Dynamic: author
Dynamic: author-email
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
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<div align="center">
  <img src="https://raw.githubusercontent.com/alpemre8/aek-img-trainer/main/logo.png" alt="AEK Auto ML Builder Logo" width="400"/>
  
  # AEK Auto ML Builder
  
  Auto ML Builder Library 
</div>

# Installation


```bash
pip install aek-auto-mlbuilder
```
For future updates:
```bash
pip install --upgrade aek-auto-mlbuilder
```

# Usage


## Create LinearRegression model

For your linear regression problems, you can use LinearRegressor class via:(for now we use syntetic data):
```python
from aek_auto_mlbuilder import LinearRegressor
from sklearn.datasets import make_regression

X, y = make_regression(n_samples=100, n_features=5, noise=0.1, random_state=42)

lr = LinearRegressor()
lr.train(X, y)
print("Best Score:", lr.best_score)
```
