Metadata-Version: 2.4
Name: mlboardkit
Version: 0.1.1
Summary: Utilities for data processing, model training, and analysis.
Author-email: Sohan <soh.venkatesh@gmail.com>
License: Apache-2.0
Project-URL: Homepage, https://github.com/sohv/scripts
Project-URL: Issues, https://github.com/sohv/scripts/issues
Keywords: machine-learning,data,nlp,ml,utilities,toolkit
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.9
Description-Content-Type: text/markdown
Requires-Dist: pandas
Requires-Dist: numpy
Requires-Dist: pyyaml
Requires-Dist: scikit-learn
Requires-Dist: psutil
Requires-Dist: imbalanced-learn
Requires-Dist: nltk
Requires-Dist: torch
Requires-Dist: tensorflow
Requires-Dist: pyarrow
Requires-Dist: openpyxl
Requires-Dist: matplotlib
Requires-Dist: requests
Requires-Dist: seaborn
Requires-Dist: ftfy
Requires-Dist: langdetect
Requires-Dist: joblib
Requires-Dist: schedule
Requires-Dist: transformers
Requires-Dist: datasets
Requires-Dist: build>=1.3.0
Requires-Dist: twine>=6.2.0
Provides-Extra: dev
Requires-Dist: pytest; extra == "dev"
Requires-Dist: ruff; extra == "dev"
Requires-Dist: mypy; extra == "dev"

# ML-Scripts

Minimal setup and installation instructions. Detailed usage has moved to `usage.md`.

## Install

```bash
# from source (editable)
pip install -e .

# from PyPI (published)
pip install mlboardkit
```

## Quick start

```python
# After installing mlboardkit, import via the mlboardkit namespace
from mlboardkit.data_utils.dataset_processor import main as dataset_processor_main
from mlboardkit.analysis_tools.metrics_utils import compute_classification_metrics

compute_classification_metrics([1,0,1],[1,0,0])
```

CLI via python -m:
```bash
python -m mlboardkit.data_utils.dataset_processor quality-check dataset.csv --report report.json
python -m mlboardkit.data_utils.data_converter convert input.json output.csv --format csv
python -m mlboardkit.analysis_tools.plot_metrics training_log.json --plot-type training --output curves.png
python -m mlboardkit.model_utils.train_model --model-name bert-base-uncased --train-file train.jsonl --epochs 3
```

Python requirement: 3.9+

Full usage and CLI examples are in `usage.md`.

