This is a framework that streamlines and facilitates the machine learning application journey with tools for data processing, fast algorithmic test, feature selection and feature engineering. It provides web ui with several backend libraries such as lazypredict library to predict multiple machine learning models on a users data preoptimization. The goal is to fasttrack the ML piipeline with tools and libraries.
Launch the web app:
To recreate this web app on your own computer, do the following.
Download and unzip contents from https://github.com/dernestbank/FastML
cd FastML-app
create a conda environment
conda create -n fastml python=3.7.9
activate env
conda activate fastml
pip install -r requirements.txt
streamlit run app.py
- One pager Multi-algorithm analysis
- Publish demo app
- Add data manupulation ( column selection, data cleaning, data transformation, etc.)
- Addd a feature engineering step to the pipeline.
- Add a feature selection step to the
- Add a model selection, optimization and hyperparameter tuning to the pipteline pipeline.
- Add a LLM feature
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.