Open source experiment tracking API with ML performance analysis.
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: Storage on SQL tables accessible with SQL, Pandas and Python API.
- Structured types: track Numpy arrays, Pandas dataframes, and series.
- Parallel execution: define and execute experiment pipelines with parameter grids.
- 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 >=3.8
- 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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