Metadata-Version: 2.1
Name: ml_experiments
Version: 0.1.2
Summary: Monitor you model training anywhere.
Home-page: https://github.com/abdalrhmanu/ml-experiments
Author: ABDELRAHMAN HABIB
Author-email: abdalrhmanusama1@gmail.com
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3
Description-Content-Type: text/markdown
License-File: LICENSE

# ML Experiments

This package is under development.


## Installation

```python
pip install ml-experiments

# or (if you are not getting the latest version)
pip install git+https://github.com/abdalrhmanu/ml-experiments.git --upgrade
```

### Notification
```python
from ml_experiments.notify import notify_desktop, notify_email

@notify_desktop(title='Testing Completed!')
  def train():
    // .. some training code ..
    return {"loss": 5}

@notify_email(recipient_emails=['emai1@email.com'], sender_email=['emai2@email.com','emai3@email.com'])
  def train():
    // .. some training code ..
    return {"loss": 5}
```

### Dataset Splitting
```python
from ml_experiments.data_prep import Dataset

dataset = Dataset(
  dataset_path=r'..\\dev\\dataset', 
  csv_path=r'..\\dev\\test.csv',
  output_directory=r'..\\dev\\out',
  output_format="dir")

# split (copy) to the defined output directory to every label
dataset.split_to_directory()

dataset2 = Dataset(
  dataset_path=r'..\\dev\\dataset', 
  csv_path=r'..\\dev\\test.csv',
  output_directory=None,
  output_format="df")

# splits to a dataframe without creating any new directory 
df, x_col, y_col = dataset2.split_to_df()

```

### Running Tests
```python
cd tests
python3 test_filename.py
```
