awesome-repositories.com
Blog
MCP
awesome-repositories.com

Discover the best open-source repositories with AI-powered search.

ExploreCurated searchesOpen-source alternativesSelf-hosted softwareBlogSitemap
ProjectMCP serverAboutHow we rankPress
LegalPrivacyTerms
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
comet-ml avatar

comet-ml/comet-examples

0
View on GitHub↗

Comet Examples

Examples of Machine Learning code using Comet.ml

Features

  • Experiment Management - Tracks datasets, code, and model experimentation history.

AI search

Explore more awesome repositories

Describe what you need in plain English — the AI ranks thousands of curated open-source projects by relevance.

Start searching with AI
  • General Machine Learning - MLOps platform for experiment tracking and model registry.
  • Model Management - Platform for model registry, lineage, and production management.
  • Experiment Tracking - Manages experiment tracking, model registries, and data lineage.
  • MLOps and Pipelines - Experiment tracking and model registry platform.
  • Data Science Tooling - Experiment tracking and model management platform.
  • Data Science Tools - Experiment tracking and model management platform.
  • 174 stars·65 forks·Jupyter Notebook·21 views

    Star history

    Star history chart for comet-ml/comet-examplesStar history chart for comet-ml/comet-examples

    How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

    Projects sharing features with Comet Examples

    These projects share indexed features with Comet Examples. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
    • iterative/mlemiterative avatar

      iterative/mlem

      718View on GitHub↗

      🐶 A tool to package, serve, and deploy any ML model on any platform. Archived to be resurrected one day🤞

      Python
      View on GitHub↗718
    • iterative/dvciterative avatar

      iterative/dvc

      15,680View on GitHub↗

      DVC is a data versioning tool and pipeline orchestrator designed to track large datasets and machine learning models. It functions as a system for managing large data artifacts by storing lightweight metadata in version control while keeping the actual binaries in a separate cache. The project serves as an experiment tracker and remote storage synchronizer, enabling the execution and comparison of machine learning iterations based on hyperparameters and performance metrics. It provides a bridge for pushing and pulling these large data artifacts between local environments and cloud or on-premi

      Python
      View on GitHub↗15,680
    • pycaret/pycaretpycaret avatar

      pycaret/pycaret

      9,857View on GitHub↗

      PyCaret is a Python AutoML platform and MLOps lifecycle manager designed to automate machine learning workflows. It functions as a low-code environment that leverages a scikit-learn native engine to execute preprocessing, training, and evaluation for tabular data. The platform distinguishes itself as an LLM-powered ML copilot, using large language model agents to analyze datasets, design experiment configurations, and explain model results. It also serves as a Kubernetes ML orchestrator and model registry, enabling the versioning of trained pipelines and their promotion to production API endp

      Pythonanomaly-detectionautomlclassification
      View on GitHub↗9,857
    • asavinov/lambdoasavinov avatar

      asavinov/lambdo

      26View on GitHub↗

      Feature engineering and machine learning: together at last!

      Python
      View on GitHub↗26
    Compare all 30 related projects→

    Frequently asked questions

    What does comet-ml/comet-examples do?

    Examples of Machine Learning code using Comet.ml

    What are the main features of comet-ml/comet-examples?

    The main features of comet-ml/comet-examples are: Experiment Management, General Machine Learning, Model Management, Experiment Tracking, MLOps and Pipelines, Data Science Tooling, Data Science Tools.

    Which projects share features with comet-ml/comet-examples?

    Projects with overlapping indexed features include: iterative/dvc — DVC is a data versioning tool and pipeline orchestrator designed to track large datasets and machine learning models.… iterative/mlem — 🐶 A tool to package, serve, and deploy any ML model on any platform. Archived to be resurrected one day🤞. pycaret/pycaret — PyCaret is a Python AutoML platform and MLOps lifecycle manager designed to automate machine learning workflows. It… astrazeneca/rexmex — A general purpose recommender metrics library for fair evaluation. astrazeneca/chemicalx — A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022). allegroai/clearml — ClearML is a comprehensive MLOps platform designed to manage the entire machine learning lifecycle. It functions as an…