Metadata-Version: 2.1
Name: comet-ml
Version: 1.0.53
Summary: Supercharging Machine Learning
Home-page: https://www.comet.ml
Author: Comet ML Inc.
Author-email: mail@comet.ml
License: UNKNOWN
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Description-Content-Type: text/x-rst
Requires-Dist: websocket-client (>=0.55.0)
Requires-Dist: requests (>=2.18.4)
Requires-Dist: six
Requires-Dist: wurlitzer (>=1.0.2)
Requires-Dist: netifaces (>=0.10.7)
Requires-Dist: nvidia-ml-py3 (>=7.352.0)
Requires-Dist: comet-git-pure (>=0.19.11)
Requires-Dist: jsonschema (>=2.6.0)
Requires-Dist: everett (==0.9) ; python_version < "3.0"
Requires-Dist: everett[ini] (>=1.0.1) ; python_version >= "3.0"

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/


