Intelligent applications employ machine learning and large-scale data processing to improve with longevity and popularity. Most of the applications you can’t live without today are intelligent, and it’s an easy bet that the applications you’ll be most excited about developing tomorrow will be intelligent as well. It’s an even easier bet that you’ll want to be deploying tomorrow’s applications on a contemporary container platform with a great developer workflow like Kubernetes.

Intelligent applications pose some new challenges for developers, but this hands-on workshop will show you how to navigate them confidently. You'll learn how to develop an intelligent application on Kubernetes from the ground up, using an open-source stack including Jupyter, Numpy, Apache Spark, and other community projects. We’ll cover:

• Why contemporary analytics frameworks are a good fit for microservice architectures;
• A crash course in some essential data processing and machine learning techniques;
• Development workflows for cross-functional teams;
• How to deploy scale-out compute clusters as part of contemporary applications; and
• Building a data-driven application in the cloud, from the ground up.

This workshop is largely self-contained:  bring some familiarity with Python and leave empowered and inspired to develop a great intelligent application. While some parts of our presentation explain concepts in the context of Apache Spark, the techniques and concepts you’ll learn are applicable to developing applications using any parallel compute framework supporting elastic scale-out.