A lightweight experimentation toolkit for data scientists.
Project description
Open source experiment tracking API with ML performance analysis to build better models faster, facilitating collaboration and transparency within the team and with stakeholders.
- Documentation: https://www.mltraq.com
- Source code: https://github.com/elehcimd/mltraq
Key features
- Fast and efficient: start tracking experiments with a few lines of code.
- Distributed: work on experiments independently and upstream them for sharing.
- Accessible: Simple SQL tables queriable with SQL, Pandas and Python API.
- Structured types: track Python types, Numpy arrays, Pandas dataframes and series.
- Parallel execution: define experiments as steps with parameter grids and execute them.
- Light checkpointing: save time by reloading and continuing your experiments anywhere.
- Steps library: enjoy pre-built steps for tracking, testing, analysis and reporting.
Requirements
- Python 3.7+
- SQLAlchemy, Pandas, and Joblib (installed as dependencies)
Installation
pip install mltraq
License
This project is licensed under the terms of the BSD 3-Clause License.
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