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Big Mac: A Distributed PaaS Framework for on Demand Big Data Processing Using Machine Learning Techniques

机译:Big Mac:使用机器学习技术进行大量数据处理的分布式PAAS框架

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摘要

In the age of start-ups and technical research, the demand for high-end computing power and loads of space is ever increasing. Machine learning techniques have become an inseparable part of the big data analytics. Setting up one's own infrastructure to deal with all this vastness is usually not feasible due to high expenses and lack of desired expertise. As a solution to this problem, this paper proposes a system for Big-Data Analytics and Machine Learning based on Hadoop and Spark frameworks that also supports Operating System (OS) Rental Services. Machine Learning (ML) services provide option to use both existing inbuilt popular models or create one's own model. OS Rental services provide users with high end infrastructure on their low-end devices on rent. The entire implementation has been made open source for ease of access and facilitating extensibility.
机译:在启动和技术研究时代,对高端计算能力和空间负荷的需求越来越多。 机器学习技术已成为大数据分析的不可分割的一部分。 由于高费用和缺乏所需的专业知识,建立一个人自己的基础设施来处理所有这些浩瀚的巨大不可行。 作为解决此问题的解决方案,本文提出了一种基于Hadoop和Spark框架的大数据分析和机器学习系统,也支持操作系统(OS)租赁服务。 机器学习(ML)服务提供了使用现有内置流行型号的选项或创建自己的模型。 OS租赁服务为用户提供高端设备上的高端基础架构在租金上。 整个实施是开放的源,便于访问和促进可扩展性。

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