Skip to main content

A lightweight tool to perform reproducible machine learning experiment using Dask.

Project description

https://img.shields.io/pypi/v/daskperiment.svg Latest Docs https://travis-ci.org/sinhrks/daskperiment.svg?branch=master https://codecov.io/gh/pandas-ml/pandas-ml/branch/master/graph/badge.svg

Overview

A lightweight tool to perform reproducible machine learning experiment using Dask.

The package is EXTREMELY unstable.

Benefits

  • User-intuitive.

    • Minimizing modifications of existing codes.

    • Performing experiments using Dask compatible API.

    • Easily handle experiments history (with pandas basic operations).

    • Requires less work to manage with Git (no need to make branch per trials).

  • Tracking experiment result and its (hyper) parameters.

  • Tracking environment.

    • OS Info

    • Python version

    • Installed package and its version

  • Tracking code context.

  • Auto saving and loading previous experiment history.

  • Parallel execution of experiment steps.

  • Sharing experiments.

    • Redis backend

Future Scope

  • Web Dashboard

  • Reproducibility check (function purity check).

  • More efficient execution.

    • Omit execution if depending parameters are the same

    • Distributed execution

Project details


Download files

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

Source Distribution

daskperiment-0.2.0.tar.gz (23.4 kB view hashes)

Uploaded Source

Built Distribution

daskperiment-0.2.0-py3-none-any.whl (44.1 kB view hashes)

Uploaded Python 3

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