Practical guides to building, running, and improving ML and AI in production.
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Effective data science and MLOps involve a number of different practices and approaches that aim to improve the efficiency and effectiveness of data science and machine learning (ML) workflows. These are the core principles and practices that can contribute to effective data science and MLOps.
Polyaxon v1.10 release of our MLOps platform brings several new features and improvements to the search and dashboarding experience.
Organization owners can now set resources quotas on their queues to limit operations concurrecy based on CPU/Memory/GPU/TPU/...
The search and filtering experience was improved with suggestions, multi-run actions, browser persistence, and many more enhancements.
The new dashboarding capabilities allows users to define advanced dashboards and visualizations widgets.
Use kubectl run to create quick pods for testing images, commands, ports, and dry-run manifests in a Kubernetes cluster.
Today, we are pleased to announce the v1.9 release of our MLOps platform, a stable version that brings several new guides for serving machine learning REST APIs on Kubernetes, running Tensorboard in sync mode, new upload command improvements, new copy mode capabilities, and a UI based connections management.
Organization owners and managers can now add, update, and delete connections directly from the UI.
Polyaxon compiler has a uniform logic to deal with pending runs.
The run and project overview pages were improved to display basic stats and progress information.
With Polyaxon v1.9, users can easily turn their params to a CLI arguments using a single flag.
Today, we are pleased to announce the v1.8 release of our MLOps platform, a stable version that brings several new rendering and UI features and scheduling enhancements.
Polyaxon v1.8 introduces several new UI enhancements including the possibility to start Tensorboard and downstream operations.
Polyaxon v1.8 comes with several new rendering capabilities.
Introducing the new graph view in Polyaxon v1.8 release.
With the release of Polyaxon v1.8 we are introducing a more customizable interface to schedule notifiers and tuners.
Today, we are pleased to announce the v1.7 release of our MLOps platform, a stable version that brings several new features, enhancements, and fixes. This release does not introduce any breaking changes and is fully compatible with previous releases.
Polyaxon v1.7 release introduces several new tracking improvements and improved documentation.
Users can now use both Polyaxon UI and Polyaxon CLI to download their runs as a CSV file.
Today, we are pleased to announce the v1.6 release of our MLOps platform, a stable version which brings several new visualization features, scalable operator concurrency enhancements, and fixes.
GitOps is an operating model for cloud-native applications built on the principle that the source of truth for an entire application should be fully managed in a source control system.
Develop a model from a reproducible baseline to a reviewed candidate, with versioned data, comparable evaluations, and a clear handoff to deployment.
Polyaxon UI has now a timeline view for pipelines, schedules and hyperparametr optimization operations.
Polyaxon v1.6 will introduce a new feature to run experiments locally without the need to have a running Polyaxon server.