Overview

Clear.ml is a comprehensive MLOps platform designed to streamline the entire machine learning lifecycle, from experiment tracking and hyperparameter optimization to model management and pipeline orchestration. It offers a unified solution for individuals and teams to manage, monitor, and reproduce ML experiments at scale.

The platform's core strength lies in its ability to automatically log and track every aspect of an experiment, including code, parameters, data, and results, ensuring full reproducibility. It also provides a centralized model registry for versioning and managing trained models, alongside tools for building and automating ML pipelines. Clear.ml enhances collaboration among data scientists and engineers by providing shared visibility and management capabilities, improving efficiency and accelerating the deployment of reliable ML models.

Key Features

  • Automatic experiment tracking and logging
  • Reproducible runs with code, data, and environment capturing
  • Centralized model registry for versioning and management
  • ML pipeline orchestration and automation
  • Hyperparameter optimization tools
  • Data versioning and management
  • Resource management and monitoring
  • Collaborative workspace for teams
  • Integration with popular ML frameworks (TensorFlow, PyTorch, Keras, scikit-learn, etc.)
  • Scalable architecture supporting self-hosted and cloud deployments

Supported Platforms

  • Web Browser (UI)
  • Python SDK/API
  • Kubernetes
  • Docker
  • Linux
  • macOS
  • Windows

Integrations

  • TensorFlow
  • PyTorch
  • Keras
  • scikit-learn
  • XGBoost
  • LightGBM
  • Pandas
  • NumPy
  • Matplotlib
  • Seaborn
  • Plotly
  • Dask
  • Spark
  • Ray
  • AWS S3
  • Google Cloud Storage (GCS)
  • Azure Blob Storage
  • Kubernetes

Pricing Tiers

Free
$0/month
  • For individuals and small projects
  • Hosted cloud service
  • Basic experiment tracking
  • Model management
Pro
Contact for Pricing
  • For teams
  • Hosted cloud service
  • Advanced experiment tracking
  • Collaborative features
  • ML pipeline orchestration
Enterprise
Contact for Pricing
  • For organizations
  • Self-hosted or VPC deployment options
  • Scalable infrastructure
  • Advanced security and compliance
  • Custom integrations and support

User Reviews

G2
ClearML is a powerful and easy-to-use platform for tracking experiments, managing models, and building pipelines. The UI is intuitive, and the automatic logging saves a lot of time.

Pros

Comprehensive features for the entire MLOps lifecycle; excellent experiment tracking and reproducibility; active community and helpful support.

Cons

The initial setup can be complex for self-hosted versions; some advanced features require a paid plan; documentation could be more detailed in certain areas.

Capterra
Great tool for keeping track of all our ML experiments. It integrates seamlessly with our existing code and workflows.

Pros

Automated logging works very well; good model registry features; helps improve team collaboration.

Cons

Can feel a bit overwhelming initially due to the number of features; cost might be a barrier for smaller teams needing advanced features.

 
 

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