Skip to main content

Supercharging Machine Learning

Project description

Comet.ml
=======

.. image:: https://img.shields.io/pypi/v/comet_ml.svg
:target: https://pypi.python.org/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

1.0.3

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-1.0.3.tar.gz (24.1 kB view details)

Uploaded Source

Built Distribution

comet_ml-1.0.3-py3-none-any.whl (33.5 kB view details)

Uploaded Python 3

File details

Details for the file comet_ml-1.0.3.tar.gz.

File metadata

  • Download URL: comet_ml-1.0.3.tar.gz
  • Upload date:
  • Size: 24.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for comet_ml-1.0.3.tar.gz
Algorithm Hash digest
SHA256 4c5f6a0363f7efab96147946d520fecf77cfe210343736d48bf88dd4a9b0b10c
MD5 88301ae73888b0d04cea505d1df85f04
BLAKE2b-256 2394d8aa74ee55610c302a4712b5648bb7ac219773a51734d8e5afe1d318e31e

See more details on using hashes here.

File details

Details for the file comet_ml-1.0.3-py3-none-any.whl.

File metadata

File hashes

Hashes for comet_ml-1.0.3-py3-none-any.whl
Algorithm Hash digest
SHA256 02df78300efd350d3f9162624738d11e6f93e9e75c6da5d39bcfcd66ee357304
MD5 eb78cb8d40352c3d1ca3789ecb312a77
BLAKE2b-256 176f61a04c489f1c8c5240bf6d9b69aae96cd673be62c980f242e80668d40f25

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