Skip to main content

Supercharging Machine Learning

Project description

Latest PyPI version

Documentation

Full documentation and additional training examples are available on http://www.comet.ml/docs/

Installation

Getting started: 30 seconds to Comet.ml

The core class of Comet.ml is an Experiment, a specific run of a script that generated a result such as training a model on a single set of hyper parameters. An Experiment will automatically log scripts output (stdout/stderr), code, and command line arguments on any script and for the supported libraries will also log hyper parameters, metrics and model configuration.

Here is the Experiment object:

from comet_ml import Experiment experiment = Experiment(api_key=”YOUR_API_KEY”)

# Your code.

We all strive to be data driven and yet every day valuable experiments results are just lost and forgotten. Comet.ml provides a dead simple way of fixing that. Works with any workflow, any ML task, any machine and any piece of code.

For a more in-depth tutorial about Comet.ml, you can check out or docs http:/www.comet.ml/docs/

License

Copyright (C) 2015-2020 Comet ML INC.

This package can not be copied and/or distributed without the express permission of Comet ML Inc.

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

comet_ml-3.31.8.tar.gz (309.3 kB view details)

Uploaded Source

Built Distribution

comet_ml-3.31.8-py2.py3-none-any.whl (374.0 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file comet_ml-3.31.8.tar.gz.

File metadata

  • Download URL: comet_ml-3.31.8.tar.gz
  • Upload date:
  • Size: 309.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.10.5

File hashes

Hashes for comet_ml-3.31.8.tar.gz
Algorithm Hash digest
SHA256 732e0a9b6611cf053ec9d1607dcba757a1de52569e259c60f8ec339702671c6a
MD5 0366b3d23dfe2f0b0dd3b55d3a842ea7
BLAKE2b-256 a31a826d4b892754979c965611bc8998f69d61295c6968a8024998c2f9ec411e

See more details on using hashes here.

File details

Details for the file comet_ml-3.31.8-py2.py3-none-any.whl.

File metadata

  • Download URL: comet_ml-3.31.8-py2.py3-none-any.whl
  • Upload date:
  • Size: 374.0 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.10.5

File hashes

Hashes for comet_ml-3.31.8-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 f060f8a8e22aaefa7530843858b59987f90e1afabfdc95ba7bdba99502ab7dca
MD5 730877869a78a81e3142a6cefe48bbc1
BLAKE2b-256 6a8fd380e08caafbdee17fc4d3e261a3212682ddfa36872527ca4dd78e3aafcb

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