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Accelerating AI/ML development at BMW Group with Amazon SageMaker Studio

Flipboard

JuMa is tightly integrated with a range of BMW Central IT services, including identity and access management, roles and rights management, BMW Cloud Data Hub (BMW’s data lake on AWS) and on-premises databases. He has a record of working with distributed teams across the globe within large enterprises.

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Exploring the AI and data capabilities of watsonx

IBM Journey to AI blog

Within watsonx.ai, users can take advantage of open-source frameworks like PyTorch, TensorFlow and scikit-learn alongside IBM’s entire machine learning and data science toolkit and its ecosystem tools for code-based and visual data science capabilities. Savings may vary depending on configurations, workloads and vendor.

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Snowflake Snowpark: cloud SQL and Python ML pipelines

Snorkel AI

And that’s really key for taking data science experiments into production. The data scientists will start with experimentation, and then once they find some insights and the experiment is successful, then they hand over the baton to data engineers and ML engineers that help them put these models into production.

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Snowflake Snowpark: cloud SQL and Python ML pipelines

Snorkel AI

And that’s really key for taking data science experiments into production. The data scientists will start with experimentation, and then once they find some insights and the experiment is successful, then they hand over the baton to data engineers and ML engineers that help them put these models into production.

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Getting Started With Snowflake: Best Practices For Launching

phData

However, if there’s one thing we’ve learned from years of successful cloud data implementations here at phData, it’s the importance of: Defining and implementing processes Building automation, and Performing configuration …even before you create the first user account.