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https://github.com/BeastByteAI/falcon
A lightweight AutoML library.
https://github.com/BeastByteAI/falcon
automl falcon-ml machine-learning ml python
Last synced: 3 months ago
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A lightweight AutoML library.
- Host: GitHub
- URL: https://github.com/BeastByteAI/falcon
- Owner: BeastByteAI
- License: mit
- Created: 2022-09-26T16:09:35.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2024-04-01T18:45:29.000Z (7 months ago)
- Last Synced: 2024-05-19T00:30:38.428Z (6 months ago)
- Topics: automl, falcon-ml, machine-learning, ml, python
- Language: Python
- Homepage: https://beastbyte.ai/
- Size: 4.53 MB
- Stars: 143
- Watchers: 10
- Forks: 11
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-AutoML - Falcon
README
# FALCON: A Lightweight AutoML Library
Falcon is a lightweight python library that allows to train production-ready machine learning models in a single line of code.
## Why Falcon ? 🔍
- Simplicity: With Falcon, training a comprehensive Machine Learning pipeline is as easy as writing a single line of code.
- Flexibility: Falcon offers a range of pre-set configurations, enabling swift interchangeability of internal components with just a minor parameter change.
- Extendability: Falcon's modular design, along with its extension registration procedure, allows seamless integration with virtually any framework.
- Portability: A standout feature of Falcon is its deep native support for [ONNX](https://onnx.ai/) models. This lets you export complex pipelines into a single ONNX graph, irrespective of the underlying frameworks. As a result, your model can be conveniently deployed on any platform or with almost any programming language, all without dependence on the training environment.
## Future Developments 🔮
Falcon ML is under active development. We've already implemented a robust and production-ready core functionality, but there's much more to come. We plan to introduce many new features by the end of the year, so stay tuned!
⭐ If you liked the project, please support us with a star!
## Quick Start 🚀
You can try falcon out simply by pointing it to the location of your dataset.
```python
from falcon import AutoML
AutoML(task = 'tabular_classification', train_data = '/path/to/titanic.csv')
```
Alternatively, you can use one of the available demo datasets.
```python
from falcon import AutoML
from falcon.datasets import load_churn_dataset, load_insurance_dataset
# churn -> classification; insurance -> regression
df = load_churn_dataset()
AutoML(task = 'tabular_classification', train_data = df)
```
## Installation 💾
Stable release from [PyPi](https://pypi.org/project/falcon-ml/)
```bash
pip install falcon-ml
```
Latest version from [GitHub](https://github.com/OKUA1/falcon)
```bash
pip install git+https://github.com/OKUA1/falcon
```
Installing some of the dependencies on **Apple Silicon Macs** might not work, the workaround is to create an X86 environment using [Conda](https://docs.conda.io/en/latest/)
```bash
conda create -n falcon_env
conda activate falcon_env
conda config --env --set subdir osx-64
conda install python=3.9
pip3 install falcon-ml
```
## Documentation 📚
You can find a more detailed guide as well as an API reference in our [official docs](https://beastbyteai.github.io/falcon/intro.html#).
## Authors & Contributors ✨
