Corrected the link suggestins

Author: Sreekanth Iyer (Ushta Te Consultancy Services)

articles/hdinsight/hadoop/apache-hadoop-deep-dive-advanced-analytics.md

@@ -57,7 +57,7 @@ HDInsight has several machine learning options for an advanced analytics workflo
 There are three scalable machine learning libraries that bring algorithmic modeling capabilities to this distributed environment:
 
 * [**MLlib**](https://spark.apache.org/docs/latest/ml-guide.html) - MLlib contains the original API built on top of Spark RDDs.
-* [**SparkML**](https://spark.apache.org/docs/1.2.2/ml-guide.html) - SparkML is a newer package that provides a higher-level API built on top of Spark DataFrames for constructing ML pipelines.
+* SparkML- SparkML is a newer package that provides a higher-level API built on top of Spark DataFrames for constructing ML pipelines.
 * [**MMLSpark**](https://github.com/Azure/mmlspark)  - The Microsoft Machine Learning library for Apache Spark (MMLSpark) is designed to make data scientists more productive on Spark, to increase the rate of experimentation, and to leverage cutting-edge machine learning techniques, including deep learning, on large datasets. The MMLSpark library simplifies common modeling tasks for building models in PySpark.
 
 ### Azure Machine Learning and Apache Hive

articles/hdinsight/spark/apache-spark-ipython-notebook-machine-learning.md

@@ -33,7 +33,7 @@ The application uses the sample **HVAC.csv** data that is available on all clust
 
 ## Develop a Spark machine learning application using Spark MLlib
 
-This application uses a Spark [ML pipeline](https://spark.apache.org/docs/2.2.0/ml-pipeline.html) to do a document classification. ML Pipelines provide a uniform set of high-level APIs built on top of DataFrames. The DataFrames help users create and tune practical machine learning pipelines. In the pipeline, you split the document into words, convert the words into a numerical feature vector, and finally build a prediction model using the feature vectors and labels. Do the following steps to create the application.
+This application uses a Spark [ML pipeline](https://downloads.apache.org/spark/docs/3.3.1/ml-pipeline.html) to do a document classification. ML Pipelines provide a uniform set of high-level APIs built on top of DataFrames. The DataFrames help users create and tune practical machine learning pipelines. In the pipeline, you split the document into words, convert the words into a numerical feature vector, and finally build a prediction model using the feature vectors and labels. Do the following steps to create the application.
 
 1. Create a Jupyter Notebook using the PySpark kernel. For the instructions, see [Create a Jupyter Notebook file](./apache-spark-jupyter-spark-sql.md#create-a-jupyter-notebook-file).
 

articles/hdinsight/spark/apache-spark-structured-streaming-overview.md

@@ -126,7 +126,7 @@ This query yields results similar to the following:
 |{u'start': u'2016-07-26T07:00:00.000Z', u'end'...	|95 |	96.980971 |	99 |
 |{u'start': u'2016-07-26T08:00:00.000Z', u'end'...	|95 |	96.965997 |	99 |  
 
-For details on the Spark Structured Stream API, along with the input data sources, operations, and output sinks it supports, see [Apache Spark Structured Streaming Programming Guide](https://spark.apache.org/docs/2.1.0/structured-streaming-programming-guide.html).
+For details on the Spark Structured Stream API, along with the input data sources, operations, and output sinks it supports, see [Apache Spark Structured Streaming Programming Guide](https://spark.apache.org/docs/latest/ss-migration-guide.html).
 
 ## Checkpointing and write-ahead logs
 
@@ -143,5 +143,5 @@ The status of all applications can also be checked with a GET request against a
 ## Next steps
 
 * [Create an Apache Spark cluster in HDInsight](../hdinsight-hadoop-create-linux-clusters-portal.md)
-* [Apache Spark Structured Streaming Programming Guide](https://spark.apache.org/docs/2.1.0/structured-streaming-programming-guide.html)
+* [Apache Spark Structured Streaming Programming Guide](https://spark.apache.org/docs/latest/ss-migration-guide.html)
 * [Launch Apache Spark jobs remotely with Apache LIVY](apache-spark-livy-rest-interface.md)