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    <title>topic Why should I use Spark MLlib for ML vs other available libraries? in Data Engineering</title>
    <link>https://community.databricks.com/t5/data-engineering/why-should-i-use-spark-mllib-for-ml-vs-other-available-libraries/m-p/24287#M16878</link>
    <description />
    <pubDate>Tue, 15 Jun 2021 20:57:14 GMT</pubDate>
    <dc:creator>User16826992666</dc:creator>
    <dc:date>2021-06-15T20:57:14Z</dc:date>
    <item>
      <title>Why should I use Spark MLlib for ML vs other available libraries?</title>
      <link>https://community.databricks.com/t5/data-engineering/why-should-i-use-spark-mllib-for-ml-vs-other-available-libraries/m-p/24287#M16878</link>
      <description />
      <pubDate>Tue, 15 Jun 2021 20:57:14 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/why-should-i-use-spark-mllib-for-ml-vs-other-available-libraries/m-p/24287#M16878</guid>
      <dc:creator>User16826992666</dc:creator>
      <dc:date>2021-06-15T20:57:14Z</dc:date>
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    <item>
      <title>Re: Why should I use Spark MLlib for ML vs other available libraries?</title>
      <link>https://community.databricks.com/t5/data-engineering/why-should-i-use-spark-mllib-for-ml-vs-other-available-libraries/m-p/24288#M16879</link>
      <description>&lt;P&gt;You don't have to. If you don't have a huge data set, there may not be much value in Spark ML over anything else. There are also other distributed modeling libraries that work on Spark like xgboost, and Horovod + TF, Keras, Pytorch. Spark ML is a good choice when you have a very large data set and need a fairly basic algorithm like logistic regression.&lt;/P&gt;</description>
      <pubDate>Thu, 17 Jun 2021 23:08:08 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/why-should-i-use-spark-mllib-for-ml-vs-other-available-libraries/m-p/24288#M16879</guid>
      <dc:creator>sean_owen</dc:creator>
      <dc:date>2021-06-17T23:08:08Z</dc:date>
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