Enterprise DNA
O Open Source Observability medium

Comet

by Community

Examples of Machine Learning code using Comet.ml

C

OSS

Comet

Added 1 June 2026

#comet-ml #deep-learning #deep-learning-algorithms #deep-learning-libraries #deep-learning-python #machine-learning #machine-learning-platform #python

Overview

Comet is an open-source collection of Jupyter Notebook examples demonstrating how to use Comet.ml for machine learning experiment tracking. The repository provides ready-to-run code snippets for logging metrics, parameters, and models across various ML frameworks.

Best for

Best for
Data scientists new to Comet.ml who want practical code examples to start tracking experiments

Use cases

  • Quickly prototype experiment tracking with Comet.ml in Jupyter
  • Learn how to log hyperparameters and metrics for model comparison
  • Integrate Comet.ml with popular ML libraries like PyTorch or TensorFlow

Notes

Comet is an open-source collection of Jupyter Notebook examples demonstrating how to use Comet.ml for machine learning experiment tracking. The repository provides ready-to-run code snippets for logging metrics, parameters, and models across various ML frameworks.

173 stars on GitHub. Last updated 2026-05-20.

Use cases

  • Quickly prototype experiment tracking with Comet.ml in Jupyter
  • Learn how to log hyperparameters and metrics for model comparison
  • Integrate Comet.ml with popular ML libraries like PyTorch or TensorFlow

Pros

  • Hands-on examples reduce setup time for new users
  • Covers multiple ML frameworks in one repo
  • Active community with 173 stars for reference

Cons

  • Limited to Jupyter Notebook format, not a standalone library
  • Examples may lag behind Comet.ml API updates
  • No documentation beyond the code comments in notebooks

Indexed from awesome-llmops and enriched against its public facts.

Pros

  • Hands-on examples reduce setup time for new users
  • Covers multiple ML frameworks in one repo
  • Active community with 173 stars for reference

Cons

  • Limited to Jupyter Notebook format, not a standalone library
  • Examples may lag behind Comet.ml API updates
  • No documentation beyond the code comments in notebooks