Skip to main content

Supercharging Machine Learning

Project description

Comet.ml
=======

.. image:: https://img.shields.io/pypi/v/comet_ml.svg
:target: https://pypi-hypernode.com/pypi/comet_ml
:alt: Latest PyPI version


Documentation
-------------

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

Installation
------------

- Sign up (free) on comet.ml and obtain an API key at https://www.comet.ml


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/
--------------


Project details


Release history Release notifications | RSS feed

This version

1.0.5

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-1.0.5.tar.gz (24.7 kB view details)

Uploaded Source

Built Distribution

comet_ml-1.0.5-py3-none-any.whl (34.2 kB view details)

Uploaded Python 3

File details

Details for the file comet_ml-1.0.5.tar.gz.

File metadata

  • Download URL: comet_ml-1.0.5.tar.gz
  • Upload date:
  • Size: 24.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for comet_ml-1.0.5.tar.gz
Algorithm Hash digest
SHA256 c6658b5c8dd847df0c4c8e5c31726c069bf0d9591443a52cf72ea88ef4b59649
MD5 320cd228052183197bc93b3b99806fe2
BLAKE2b-256 7b58bc3147f8c2d77a676809eb9d3e54f0aa36143e8cb4482d06587cb1321621

See more details on using hashes here.

File details

Details for the file comet_ml-1.0.5-py3-none-any.whl.

File metadata

File hashes

Hashes for comet_ml-1.0.5-py3-none-any.whl
Algorithm Hash digest
SHA256 8cf5af48a3f08c516bb9dd3409c224ad18d3a86a397d584a36001368ced126d7
MD5 43e73415c4bfa6da88d80f979f25fe1c
BLAKE2b-256 06202cd98183464a1549c68d766c59938a09995465ae2c6f00210cfa3da5eab6

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