MMLSpark: Unifying Machine Learning Ecosystems at Massive Scales

We introduce Microsoft Machine Learning for Apache Spark (MMLSpark), anecosystem of enhancements that expand the Apache Spark distributed computinglibrary to tackle problems in Deep Learning, Micro-Service Orchestration,Gradient Boosting, Model Interpretability, and other areas of moderncomputation. Furthermore, we present a novel system called Spark Serving thatallows users to run any Apache Spark program as a distributed, sub-millisecondlatency web service backed by their existing Spark Cluster. All MMLSparkcontributions have the same API to enable simple composition across frameworksand usage across batch, streaming, and RESTful web serving scenarios on static,elastic, or serverless clusters. We showcase MMLSpark by creating a method fordeep object detection capable of learning without human labeled data anddemonstrate its effectiveness for Snow Leopard conservation.

How JRebel Speeds Up Development

JRebel is a JVM plugin that speeds up the development of Java applications by skipping the build and redeploy steps. Watch this video to learn more.

Adapter Design Pattern In Java - Programmer Girl

Introduction: The Adapter design pattern is a structural design pattern that helps us to connect to the legacy or third-party code that exposes a similar functionality through a different interface. A real-world analogy for an adapter is the one we use to connect our USB cable to an ethernet port. While designing an object-oriented application, …

Integration tests with Docker

This post gives an overview how we at Karakun use Docker to create integration tests for JavaEE / JakartaEE based libraries and frameworks.