图 书 馆
将R用于可扩展数据科学：单机到Hadoop Spark集群Using R for Scalable Data Science: Single Machines to Hadoop Spa0rk Clusters |
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| 课程网址: | http://videolectures.net/kdd2017_hands_on_tutorial_scalable_data/ |
| 主讲教师: | Hang Zhang |
| 开课单位: | 微软 |
| 开课时间: | 2017-11-14 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | In this tutorial, we will demonstrate how to create scalable, end-to-end data analysis processes in R on single machines as well as in-database in SQL Server and on Hadoop clusters running Spark. We will provide hands-on exercises as well as code in a public GitHub repository for attendees to adopt in their data science practice. In particular, the attendees will see how to build, persist, and consume machine learning models using distributed machine learning functions in R. R is one of the most used languages in the data science, statistical and machine learning (ML) community. Although open-source R (CRAN library) now has in excess of 10,000 packages and functions for statics and ML, when it comes to scalable analysis using R, or deployment of trained models into production, many data scientists are blocked or hindered by (a) its limitations of available functions to handle large datasets efficiently, and (b) knowledge about the appropriate computing environments to scale R scripts from desktop analysis to elastic and distributed cloud services. In this tutorial, we will discuss how to create end-to-end data science solutions that utilize distributed compute resources. During the tutorial, we will provide presentations, worked-out examples, and hands-on exercises with sample code. In addition, we will provide a public GitHub code repository that attendees will be able to access and adapt to their own practice. We believe this tutorial will be of strong interest to a large and growing community of data scientists and developers who are using R for creating and deploying analytical solutions. |
| 关 键 词: | 数据分析; 数据实践; 机器学习 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2023-07-19：chenxin01 |
| 最后编审: | 2023-07-19：chenxin01 |
| 阅读次数: | 21 |