Metadata-Version: 2.4
Name: ml_auto_trainer
Version: 0.1.0
Summary: A simple auto machine learning trainer that builds models with one function call.
Home-page: https://github.com/shivchaudhari-ai/ml_auto_trainer
Author: Shivam Vinod Chaudhari
Author-email: shivam7744998850@gmail.com
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Requires-Dist: scikit-learn
Requires-Dist: pandas
Requires-Dist: xgboost
Requires-Dist: numpy
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

# ml_auto_trainer ðŸš€

A one-function AutoML package that builds, trains, and evaluates ML models automatically.

## âœ¨ Features
- Automatically detects problem type (classification or regression)
- Supports popular models (RandomForest, XGBoost, Logistic, Linear, KNN, GBM)
- Prints metrics automatically

## ðŸ§  Usage

```python
from ml_auto_trainer.auto_trainer import auto_train
import pandas as pd
from sklearn.datasets import load_iris

# Load data
data = load_iris()
X = pd.DataFrame(data.data, columns=data.feature_names)
y = data.target

# Train model
model = auto_train(X, y, model_name='xgboost')
