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SynapseML

Simple and Distributed Machine Learning

Coming from MMLSpark? We have been renamed to SynapseML!
from synapse.ml.cognitive import *
sentiment_df = (TextSentiment()
.setTextCol("text")
.setLocation("eastus")
.setSubscriptionKey(key)
.setOutputCol("sentiment")
.setErrorCol("error")
.setLanguageCol("language")
.transform(input_df))
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Simple

Simple

Quickly create, train, and use distributed machine learning tools in only a few lines of code.

Scalable

Scalable

Scale ML workloads to hundreds of machines on your Apache Spark cluster.

Multilingual

Multilingual

Use SynapseML from any Spark compatible language including Python, Scala, R, Java, .NET and C#.

Open

Open

SynapseML is Open Source and can be installed and used on any Spark 3 infrastructure including your local machine, Databricks, Synapse Analytics, and others.

Installation

Written in Scala, and support multiple languages. Open source and cloud native.

Note: SynpaseML will be built-in for Azure Synapse soon.

SynapseML can be conveniently installed on Synapse:
%%configure -f
{
"name": "synapseml",
"conf": {
"spark.jars.packages": "com.microsoft.azure:synapseml_2.12:0.9.4",
"spark.jars.repositories": "https://mmlspark.azureedge.net/maven",
"spark.jars.excludes": "org.scala-lang:scala-reflect,org.apache.spark:spark-tags_2.12,org.scalactic:scalactic_2.12,org.scalatest:scalatest_2.12",
"spark.yarn.user.classpath.first": "true"
}
}
Please also include `synapseml==0.9.4` in your requirements.txt file for usage of PySpark. [Install Python libraries in Synapse]