Learn how to build and scale intelligent service-rich applications with less custom codeMasterclass Space 1
The new landscape of intelligent services let you build and scale applications and services through integration and interoperability, while relying less on custom development. Thomas Dyar shows you how you can leverage the wide array of services available in your big data applications, highlighting the critical aspects of interoperability when combining multiple services that consume disparate types of data. Then you'll build an intelligent application using Spark for machine learning, and the InterSystems IRIS data platform for service coordination and data management, among other technologies. What you'll learn, and how you can apply it
• Explore intelligent services concepts and best practices for designing analytic applications
• Learn design patterns for ingesting, collecting, storing, analyzing, and visualizing big data
• Build a data-intensive application using technologies such as InterSystems IRIS and SparkML This workshop is for you because...
• You're a big data architect, data analytics professional, or data scientist who wants to learn more about incorporating intelligent services into applications. Prerequisites:
• A basic understanding of microservices and related web technologies • Experience with Spark (useful but not required) Hardware and/or installation requirements:
• A laptop Outline • Intro to big data and Spark
• Interoperability concepts • Data ingestion and storage • Connecting services and machine learning models to build an intelligent application
Do we really need to hoard all data? Is machine learning inevitably connected to a degree of privacy violation? No, decentralized learning, differential privacy, and federated learning are here to help. Sounds all Greek to you? Join us in our masterclass!