Supercharging Machine Learning
Full documentation and additional training examples are available on http://www.comet.ml/docs/
- 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/
Copyright (C) 2015-2019 Comet ML INC.
This package can not be copied and/or distributed without the express permission of Comet ML Inc.
Release history Release notifications
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|Filename, size||File type||Python version||Upload date||Hashes|
|Filename, size comet_ml-3.0.2-py3-none-any.whl (170.8 kB)||File type Wheel||Python version py3||Upload date||Hashes View hashes|
|Filename, size comet_ml-3.0.2.tar.gz (142.7 kB)||File type Source||Python version None||Upload date||Hashes View hashes|