Anaconda Enterprise 5.2 releases with special focus on machine learning in production

With just a month after the release of Anaconda Distribution 5.2, the team at Anaconda, Inc excitingly announces the enterprise release of Anaconda Enterprise 5.2.

The newer version of enterprise release boosts its capabilities with GPU-acceleration feature, cloud-native model management and scaling machine learning models. This release is expected to power-up the enterprises with high-speed digital interactions required in Artificial Intelligence and Machine Learning operations.

New features in Anaconda Enterprise 5.2:

GPU acceleration with Cloud-native support - Enables GPU computation for complex and heavy deep learning workloads. It provides secure and efficient utilization of GPU clusters thereby delivers efficient ways to perform large machine learning operations at scale.

Job schedule - This allows priority jobs to be allocated with enough CPU and GPU allocation along with supporting regular deployments of recurring jobs.

Easy Git integration - Provides support for collaborating your existing version control and continuous integration tools such as Bitbucket and Git

With such new features, millions of scientists can take their machine learning projects from training to production level with complete security and absolute governance. The open source platform Anaconda Distribution is already benefiting over 6 million data science users to develop and optimize their machine learning models on large datasets.

Anaconda Enterprise is the only product on the market that allows data scientists to go from laptop for model development to a 1000-node GPU cluster for training to production deployment—all with full reproducibility and governance.
According to Anaconda, Inc., “Anaconda Enterprise is the only platform to combine core AI technologies, automated governance, and reproducibility, and cloud-native approaches to make data science teams as productive as possible. Anaconda Enterprise empowers organizations to develop, govern, and automate ML/AI pipelines from laptop to production, quickly delivering insights into the hands of business leaders and decision-makers.”

To know more on the administrator facing and backend improvement changes, you can read the release note which would be very soon available on the Anaconda Documentation. Until then, you can also refer to the official announcement about this release on Anaconda’s blog.

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