Cloudera

NOVEMBER 17, 2021

Some companies are starting to segregate the responsibilities of the unicorn data scientist into multiple roles (data engineer, ML engineer, ML architect, visualization developer, etc.), We are very excited to announce the release of five, yes FIVE new AMPs, now available in Cloudera Machine Learning (CML).

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Cloudera

FEBRUARY 25, 2021

Today’s enterprise data science teams have one of the most challenging, yet most important roles to play in your business’s ML strategy. In our current landscape, businesses that have adopted a successful ML strategy are outperforming their competitors by over 9%. The implications of ML on the future of business are clear.

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Cloudera

MAY 17, 2021

CDP (Cloudera Data Platform) Private Cloud 1.2 In this blog, we’ll cover the complete range of new capabilities and updates for CDP Private Cloud as a whole (the platform) as well as for both the CDW (Cloudera Data Warehouse) and CML (Cloudera Machine Learning) services. CML – Applied ML Prototypes.

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Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. In this article, we explore model governance, a function of ML Operations (MLOps). Machine Learning Model Lineage. Figure 01: Is this a chihuahua or a muffin? Model Interpretability.

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Cloudera

OCTOBER 6, 2022

Gartner : “Digital transformation can refer to anything from IT modernization (for example, cloud computing), to digital optimization, to the invention of new digital business models.”. For example, we have some customers using their data platform originally established for compliance initiatives to drive new use cases.

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Cloudera

OCTOBER 26, 2022

It’s no secret that advancements like AI and machine learning (ML) can have a major impact on business operations. In Cloudera’s recent report Limitless: The Positive Power of AI , we found that 87% of business decision makers are achieving success through existing ML programs. What are AMPs and why do they help?

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Cloudera

OCTOBER 3, 2022

You’ve found an awesome data set that you think will allow you to train a machine learning (ML) model that will accomplish the project goals; the only problem is the data is too big to fit in the compute environment that you’re using. So what do you do? Prerequisites. Each of these common Python libraries has a Dask equivalent.

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