Skip to main content

A lightweight experimentation toolkit for data scientists.

Project description

MLTRAQ Logo

Test Test Test Test Test Test


Open source experiment tracking API with ML performance analysis to build better models faster, facilitating collaboration and transparency within the team and with stakeholders.



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.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mltraq-0.0.37.tar.gz (79.1 kB view details)

Uploaded Source

Built Distribution

mltraq-0.0.37-py3-none-any.whl (86.0 kB view details)

Uploaded Python 3

File details

Details for the file mltraq-0.0.37.tar.gz.

File metadata

  • Download URL: mltraq-0.0.37.tar.gz
  • Upload date:
  • Size: 79.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.2.2 CPython/3.10.7 Darwin/21.6.0

File hashes

Hashes for mltraq-0.0.37.tar.gz
Algorithm Hash digest
SHA256 568f0b89efe3bca61b504e4ef323afa2fb18dce5b84ee6fadd0ac8a1e8d541a0
MD5 2865fd51e4b8da223219fcd5884edc63
BLAKE2b-256 5ed74e5930b3794e6e4fc9ebb97581462f4422e7c9f05f1c33e67f76e653fab1

See more details on using hashes here.

File details

Details for the file mltraq-0.0.37-py3-none-any.whl.

File metadata

  • Download URL: mltraq-0.0.37-py3-none-any.whl
  • Upload date:
  • Size: 86.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.2.2 CPython/3.10.7 Darwin/21.6.0

File hashes

Hashes for mltraq-0.0.37-py3-none-any.whl
Algorithm Hash digest
SHA256 3cc2974eec3fda587533b3ba7b234c6ffdbeabca13e47743df4ff1d0d6548d41
MD5 1332b0acf46c87a707b3adf6eff94351
BLAKE2b-256 1b1c51a1d5707d5adf8a5f3363be6043ae50429e7aa1a35ba7cb0ee7fd2a088d

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page