Difference between revisions of "Spark MLlib"
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* [[Libraries & Frameworks]] | * [[Libraries & Frameworks]] | ||
* [http://spark.apache.org/mllib/ Spark MLlib] | * [http://spark.apache.org/mllib/ Spark MLlib] | ||
| − | * [[Ray | + | * [[Ray - UC Berkeley RISELab]] |
Apache Spark's scalable machine learning library. MLlib fits into Spark's APIs and interoperates with NumPy in Python (as of Spark 0.9) and R libraries (as of Spark 1.5). You can use any Hadoop data source (e.g. HDFS, HBase, or local files), making it easy to plug into Hadoop workflows. | Apache Spark's scalable machine learning library. MLlib fits into Spark's APIs and interoperates with NumPy in Python (as of Spark 0.9) and R libraries (as of Spark 1.5). You can use any Hadoop data source (e.g. HDFS, HBase, or local files), making it easy to plug into Hadoop workflows. | ||
Latest revision as of 10:34, 17 August 2020
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Apache Spark's scalable machine learning library. MLlib fits into Spark's APIs and interoperates with NumPy in Python (as of Spark 0.9) and R libraries (as of Spark 1.5). You can use any Hadoop data source (e.g. HDFS, HBase, or local files), making it easy to plug into Hadoop workflows.
