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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 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.
from falcon import AutoML
AutoML(task = 'tabular_classification', train_data = '/path/to/titanic.csv')
Alternatively, you can use one of the available demo datasets.
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
pip install falcon-ml
Latest version from GitHub
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
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.
