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/
--------------
=======
.. 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/
--------------
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