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MLlib

MLlib is Spark's machine learning (ML) library that make practical machine learning scalable & provides ML Algorithms.

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#Data Science And Machine Learning #Data Science Tools #Python Tools #Software Libraries

MLlib Reviews and details

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  • MLlib Landing page
    Landing page //
    2023-06-12

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Videos

Using Spark Mllib Models in a Production Training and Serving Platform Experiences and ExtensionsA

Spark MLlib

Announcement: LIVE on 26th July [ Spark SQL & MLLib ]

Social recommendations and mentions

We have tracked the following product recommendations or mentions on various public social media platforms and blogs. They can help you see what people think about MLlib and what they use it for.
  • Predicting Diabetes In Patients - Apache Spark Machine Learning - 4 Easy Steps To Do This!
    The MLlib library gives us a very wide range of available Machine Learning algorithms and additional tools for standardisation, tokenisation and many others (for more information visit the official website Apache Spark MLlib). (Apache Spark Machine Learning predicting diabetes in patients). Source: about 2 years ago
  • How to distribute ML tasks across CPU and GPU?
    Totally agree with the current responses, especially for the purposes of understanding exactly what's going on under the hood, but did want to just call out the fact that you can simply use a machine learning library that's implemented in a distributed way. Examples would be MLlib From Spark and h2o. H2O in particular will take care of pretty much everything for you in terms of initializing a cluster, and has a... Source: about 2 years ago

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This is an informative page about MLlib. You can review and discuss the product here. The primary details have not been verified within the last quarter, and they might be outdated. If you think we are missing something, please use the means on this page to comment or suggest changes. All reviews and comments are highly encouranged and appreciated as they help everyone in the community to make an informed choice. Please always be kind and objective when evaluating a product and sharing your opinion.

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