In this demo paper, we introduce the DARPA D3M program for automatic machine learning (ML) and JPL's MARVIN tool that provides an environment to locate, annotate, and execute machine learning primitives for use in ML pipelines. MARVIN is a web-based application and associated back-end interface written in Python that enables composition of ML pipelines from hundreds of primitives from the world of Scikit-Learn, Keras, DL4J and other widely used libraries. MARVIN allows for the creation of Docker containers that run on Kubernetes clusters within DARPA to provide an execution environment for automated machine learning. MARVIN currently contains over 400 datasets and challenge problems from a wide array of ML domains including routine classification and regression to advanced video/image classification and remote sensing.
翻译:在这份演示文件中,我们介绍了DARPA D3M自动机器学习(ML)和JPL的MARVIN工具DARPA D3M程序,为定位、批注和执行机器学习原始材料以用于ML管道提供了环境。MARVIN是一个网络应用程序,也是以Python书写的相关后端界面,它使得ML管道能够由来自Sciikit-Learn、Keras、DL4J和其他广泛使用图书馆的数百个原始材料组成。MARVIN允许在DARPA的Kubernetes集群上建立多克集装箱,为自动机器学习提供一个执行环境。MARVIN目前包含400多个ML域的数据集和挑战,包括常规分类和回归到先进的视频/图像分类和遥感。