SynapseML is an open-source framework for building massively scalable machine learning (ML) pipelines. SynapseML provides simple, modular, and distributed APIs for a wide range of machine learning applications such as text analytics, vision, anomaly detection, and many more. SynapseML is built on the distributed computing architecture Apache Spark (big data analytics platform) and has the same API as the SparkML/MLLib library, allowing you to simply incorporate SynapseML models into existing Apache Spark workflows. SynapseML is a tool ecosystem aimed at enhancing the Apache Spark distributed computing platform in various new areas. SynapseML extends the Spark ecosystem with several deep learning and data science technologies. It allows for the creation of advanced and highly scalable predictive and analytical models for a wide range of data sources. SynapseML additionally expands the Spark Ecosystem's networking capabilities. In this line, SynapseML offers simple SparkML transformers for a broad range of services. The Spark Serving project allows high throughput, sub-millisecond latency web services, supported by your Spark cluster, for production-grade deployment. Introduction of Big Data Analytics Introduction of Apache Spark What is Synapse ML Components of SynapseML Demo: SynapseML SynapseML for Responsible AI