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-3.3.3.tar.gz (211.2 kB view details)

Uploaded Source

Built Distribution

comet_ml-3.3.3-py2.py3-none-any.whl (250.3 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file comet_ml-3.3.3.tar.gz.

File metadata

  • Download URL: comet_ml-3.3.3.tar.gz
  • Upload date:
  • Size: 211.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.25.1 setuptools/47.1.1 requests-toolbelt/0.9.1 tqdm/4.56.2 CPython/3.8.3

File hashes

Hashes for comet_ml-3.3.3.tar.gz
Algorithm Hash digest
SHA256 3d1c6879c70f963fd2667ca76879a40dac4dd8046948b37e74f21723b5890a38
MD5 19d361c4a25a8b16032f0f63bde09652
BLAKE2b-256 835e941a74d0f86dc93c0bdd8ed1753191c9f04c7338f5226270cee6d3e1233a

See more details on using hashes here.

File details

Details for the file comet_ml-3.3.3-py2.py3-none-any.whl.

File metadata

  • Download URL: comet_ml-3.3.3-py2.py3-none-any.whl
  • Upload date:
  • Size: 250.3 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.25.1 setuptools/47.1.1 requests-toolbelt/0.9.1 tqdm/4.56.2 CPython/3.8.3

File hashes

Hashes for comet_ml-3.3.3-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 92f6fe110f00efce36a87c085e1c054fa6ffca1cc093f8373b6b80888767660d
MD5 75b71711fdfa11c33809db75387a8ef9
BLAKE2b-256 c86e7c4314622a4a422a47ccc6f19795fffc34208c7d7d1f7677cd23891e7b11

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