Tracking »
Automatically track key model metrics, hyperparams, visualizations, artifacts and resources, and version control code and data.
Orchestration »
Maximize the usage of your cluster by scheduling jobs and experiments via our CLI, dashboard, SDKs, or REST API.
Optimization »
Use our optimization algorithms to effectively run parallel experiments and find the best model.
Insights »
Visualize, search, and compare experiment results, hyperparams, training data and source code versions, so you can quickly analyze what worked and what didn’t.
Model management »
Consistently develop, validate, deliver, and monitor models to create a competitive advantage.
Collaboration »
Instead of ad-hoc scripts, collaborate with the rest of your team and enable knowledge distribution practices in your organization.
Management »
Reflect your organization's structure and manage permissions and quotas for your resources and cluster access.
Compliance »
Reproduce results and meet regulatory compliance without any added work.
Scalability »
Scale your resources as needed, and run jobs and experiments on any platform (AWS, Microsoft Azure, Google Cloud Platform, and on-premises hardware).
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Polyaxon let's you automatically track key model metrics, hyperparams, visualizations, artifacts and resources, and version control code and data.
Once Polyaxon has been integrated into your model, each experiment and every trained model’s set of hyperparameters is recorded and viewable from the dashboard. Never again will you need to search through local config files to find that set of hyperparameters which performed well.
Lightweight Integration
Add Polyaxon to your code with just a few lines, and we'll automatically capture and log system metrics for you.
Log anything
- Enable hyperparams and metrics logging for performance measurement
- Data, artifacts, and outputs logging for pipelines and reproducible experiments
- Centralize your runs’ logs
Compare runs
- Search and get better understanding of your experiments performance
- Enable access to multiple dashboarding and vizualuasation tools
Integrate with with git
Link between code and model in very easy without altering your workflow
Maximize the usage of your cluster by scheduling jobs and experiments via our CLI, dashboard, SDKs, or REST API.
Develop models at any scale
- Leverage advance scheduling schemas without wasting time on devops
- Schedule parallel and distributed runs for rapid iterations
- Maximize utilization of computing resources to scale the volume, variety, and complexity of models in development and production
Elastic and Auto Scaling
- Grow and shrink compute resources elastically as needed
- Add GPUs and resources to your cluster as needed
Hybrid Resources
- Train experiments on the cloud, on premise, or local machines and keep track of results and artifacts
- Manage all resources and workflows in a single interface
Restart experiments and jobs
- Polyaxon knows how to schedule an experiment to run with the same conjugation and parameters to reach the same results
- Automate repeatable tasks that do not benefit from domain expertise so your experts focus their effort where it will have the greatest impact
Visualize, search, and compare experiment results, hyperparams, training data and source code versions, so you can quickly analyze what worked and what didn’t.
Reproduce and analyze your experiments with the built-in insights dashboard.
Monitor, track, and analyze every single optimization experiment with the experiment insights dashboard. Reproducing experiments and results is one of the greatest challenges for the best modeling teams, and the built-in insights dashboard provides a visual interface for experimentation.
Enable analysis of past experiments through a powerful and interactive dashboard
- Use various visualizations and graphs to derive insights from the experiments
- Get accurate information about the importance of your Parameters
Experiment comparison
Compare experiment results, hyperparams, versions of training data and source code, so you can quickly analyze what worked and what didn’t
Auto-documentation
Automatically discovers and documents the success metrics, hyperparams, source code, data, visualizations, artifacts and resources used in each experiment
Experiment history
See the full experiment history at a glance, including when, who and where
Plugins for additional graphing and visualization
you can easily start various tools to enable data explorations and metrics visualizations
Insights for single researcher as well as large organizations
- View other teammates’ experiments
- Have enterprise-grade access control, team management, and usage monitoring features for data science managers and executives.
A single system for your entire experimentation process