agolocuonghoang / comet-content

Content for Comet Blog

Welcome to the Comet.ml Tutorial Center!

This repository contains example datasets and models that help guide you through the experience of using Comet.ml towards reproducible and interesting machine learning experiments.

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 - we work 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:

• Getting started with the Experiment class

• NEW Using fastText and Comet.ml to classify relationships in Knowledge Graphs using preprocessed data from https://github.com/thunlp/KB2E

FAQ

1. What do I need in order to get started?

• Sign up (free) on comet.ml and obtain an API key

• Install Comet.ml from PyPI: Comet.ml python SDK is compatible with: Python 2.7-3.6.

pip install comet_ml

pip3 install comet_ml

2. Where can I find the docunentation for Comet.ml?

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

3. Where should I go to report bugs or ask questions? We have a public repo that we monitor for bug reports + also feature enhancement requests here: https://github.com/comet-ml/issue-tracking/issues

We also encourage you to join our public Slack community where you can ask questions to the entire Comet.ml team and see how other users are using Comet.ml!