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Microsoft integrates Azure Machine Learning with Snowflake

Microsoft integrates Azure Machine Learning with Snowflake
Photo Credit: Pixabay
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Microsoft has integrated Azure Machine Learning with Snowflake, a cloud computing-based data cloud company, enabling users to import data with a single command.

According to a blog post on Microsoft’s official website, data scientists using Snowflake as their data warehouse solution can now access Azure ML capabilities without the need for third-party libraries or data engineering teams.

Microsoft aims to establish Azure cloud as the top choice for businesses looking to execute their AI and machine learning operations.

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In the blog post, Amar Badal, senior manager for Azure Machine Learning, stated, "Data scientists from organizations that have adopted Snowflake as their data warehouse solution can now explore Azure ML capabilities without relying on third-party libraries or engaging data engineering teams."

The integration also allows data scientists to utilize Azure’s machine learning algorithms and models to build, train, and deploy machine learning models for production.

However, the integration is currently in preview and is expected to become generally available in the coming months.

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This announcement follows Microsoft's expanded partnership with Nvidia and the public release of Azure Machine Learning's foundation models at the Build 2023 conference. The company has also made improvements to its artificial intelligence training capabilities.

Microsoft has simplified the foundation models, making it easier for businesses to import data from external sources into Azure Machine Learning for AI development and training.

Cloud services are increasingly popular among enterprises adopting AI technologies because they offer access to hardware optimized for AI workloads, which can be costly and challenging to manage on-premises. As the demand for large language models (LLMs) and generative AI applications like ChatGPT continues to grow, more enterprises are expected to turn to hyperscale cloud providers as a cost-effective way to keep up with this rapidly accelerating trend.

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