This new integration promotes machine learning initiatives into organizations’ software development lifecycle. Users now have the benefits of a centralized code repository such as increased ML portability, compliance, and security for enterprise ML projects. The integration adheres to DevOps best practices for managing ML models in production, thus shortening the time-to-value for data science initiatives.
SEATTLE, Feb. 20, 2020 (GLOBE NEWSWIRE) -- Algorithmia announces a major update to its Enterprise platform. The platform, which allows data scientists and ML engineers to easily automate the DevOps, management, and deployment of AI/ML models in the language of their choice, now integrates with GitHub.
By expanding its source code management capabilities, Algorithmia is making it easier for data scientists and ML engineers to organize code, track changes, collaborate with colleagues and rapidly deliver high-quality AI-based applications, with the added benefits of GitHub in combination with Algorithmia.
GitHub brings together the world’s largest community of developers to discover, share and build better software, and is a trusted repository for software developers and data science teams. By integrating with GitHub, Algorithmia enables data science deployment processes to follow the same software development lifecycle (SDLC) organizations already leverage, via a seamless integration.
With the Algorithmia–GitHub integration, users can store their code on GitHub and deploy it directly to Algorithmia and Algorithmia Enterprise. In this way, teams working on ML can participate in their organization’s SDLC. That is, multiple users can easily contribute, collaborate on a centralized code base, and ensure code quality with best practices like code reviews through pull requests and issue tracking.
Users can also take advantage of GitHub’s governance applications around dependency management to ensure their models aren’t at risk of utilizing package versions with deprecated features.
“As more applications are driven by machine learning, it will become increasingly important for these projects to be part of an organization’s software development lifecycle,” said Diego Oppenheimer, CEO of Algorithmia. “Model deployment and management should be as simple as checking-in any other code. With Algorithmia’s source code management integrations, it will be. Data scientists will be as agile as any software team.”
The GitHub integration is now available to algorithmia.com public users and for existing Algorithmia Enterprise customers.
About Algorithmia
Algorithmia is a single solution for all stages of the MLOps and management lifecycle, enabling data management, deployment, management, and operations teams to work concurrently on the same machine learning project. Algorithmia enables users to connect data sources, orchestration engines, and step functions and deploy models from major frameworks, languages, platforms, and tools. Over 90,000 engineers and data scientists have used Algorithmia’s platform to date, including the United Nations, government intelligence agencies, and Fortune 500 companies. For more information, visit www.algorithmia.com.
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