基于Docker的大数据AI教学与实验系统
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摘要
大数据AI教学与实验系统是一个基于Docker容器技术研发的大数据人工智能在线教学、实验和科研的云平台。该云平台支持主流深度学习框架Tensorflow,能快速部署深度学习的训练环境,共享GPU计算资源,支持多人同时在线学习和实验。云平台还支持大数据hadoop实验,提供hadoop的安装和应用实验。在云平台上,老师可展开大数据、人工智能领域的教学与科研,学生可完成相关课程的学习、实验。本系统能有效降低大数据AI教学和科研的难度,利于高校大数据、人工智能的人才培养和科研创新。
The Big Data AI Teaching and Experiment System is a cloud platform for online teaching, experimentation and research of big data artificial intelligence based on Docker container technology. The cloud platform supports the mainstream deep learning framework Tensorflow, which can quickly deploy a deep learning training environment, share GPU computing resources, and support multi-person simultaneous online learning and experimentation. The cloud platform also supports big data Hadoop experiments, providing Hadoop installation and application experiments. On the cloud platform, teachers can carry out teaching and research in the field of big data and artificial intelligence. Students can complete the study and experiment of relevant courses. The system can effectively reduce the difficulty of big data AI teaching and scientific research, and is conducive to the talent training and scientific research innovation of university big data and artificial intelligence.
The Big Data AI Teaching and Experiment System is a cloud platform for online teaching, experimentation and research of big data artificial intelligence based on Docker container technology. The cloud platform supports the mainstream deep learning framework Tensorflow, which can quickly deploy a deep learning training environment, share GPU computing resources, and support multi-person simultaneous online learning and experimentation. The cloud platform also supports big data Hadoop experiments, providing Hadoop installation and application experiments. On the cloud platform, teachers can carry out teaching and research in the field of big data and artificial intelligence. Students can complete the study and experiment of relevant courses. The system can effectively reduce the difficulty of big data AI teaching and scientific research, and is conducive to the talent training and scientific research innovation of university big data and artificial intelligence.
引文
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[2]闫实,付佳,石莉.大数据环境下基于智慧校园的教学改革[J].软件,2018,39(2):208-211.
[3]国发[2017]35号.新一代人工智能发展规划[S].北京:国务院,2017.
[4]汪子尧,贾娟.人工智能的前生、今世与未来[J].软件,2018,39(2):223-226.
[5]腾讯研究院.人工智能[M].北京:中国人民大学出版社,2017.
[6]刘鹏.深度学习[M].北京:电子工业出版社,2017.
[7]朱福喜.人工智能[M].北京:清华大学出版社,2017.
[8]李凡长,钱旭培,谢琳,何书萍.机器学习理论及应用[J].计算机工程与科学,2012,Vol.34(09).
[9]严冬梅.数据库原理[M].北京:清华大学出版社,2011.
[10]刘思尧,李强,李斌.基于Docker技术的容器隔离性研究[J].软件,2015,36(4):110-113.