Skip to main content
Join the official 2020 Python Developers SurveyStart the survey!

Facilitating reproducible AutoML research.

Project description

AutoML Utils

While machine learning is facing a reproducibility crisis, the problem is exacerbated in the subdiscipline of automated machine learning [1, 2] where the number of potential hyperparameters and variations in search and training regimens can be vast.

When combined with the duplication of code across projects, often with subtle differences in implementation, it can be challenging to resolve whether changes in performance stem from improved methodology or from changes in configuration.

This repository aims to facilitate these comparisons by providing reference implementations of commonly used components. It is designed to be minimal and unopinionated to ensure maximum flexibility for the researcher.

Note: This work is intentionally being released in an early state of development to enable use in other projects and guide future efforts based on feedback received. 

Project details


Download files

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

Files for automl-utils, version 0.1.0a1
Filename, size File type Python version Upload date Hashes
Filename, size automl_utils-0.1.0a1-py3-none-any.whl (18.3 kB) File type Wheel Python version py3 Upload date Hashes View
Filename, size automl-utils-0.1.0a1.tar.gz (13.0 kB) File type Source Python version None Upload date Hashes View

Supported by

Pingdom Pingdom Monitoring Google Google Object Storage and Download Analytics Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page