查看“大数据与机器智能”的源代码

==教学团队==
互联网+实验室 [http://net.icenter.tsinghua.edu.cn iNetLab]

[https://www.researchgate.net/profile/Zhen_Chen16/ 陈震]  
马晓东 章屹松 王蓓蓓 高英

助教：郑文勋 李辰星

==协同开发==
iCenter-cloud [http://cloud.icenter.tsinghua.edu.cn  iCenter-cloud]

Gitlab [http://gitlab.icenter.tsinghua.edu.cn  GitLab]

=教学目标=

以完成一种以大数据为基础的智能系统的原型开发为目标，在实践中运用大数据智能理论与技术。团队成员学习大数据系统与机器智能的理论知识和专业技能，完成项目团队结构设计和原型开发的实践环节，全面提高学生的技术实践能力。

=课程内容=

==技术本质浅论==

==课程实践准备==
===Azure云平台使用===

===Flask Web服务器搭建===

==大数据索引==
===bitmap index===

#Chambi, Samy, Daniel Lemire, Owen Kaser, and Robert Godin. "Better bitmap performance with Roaring bitmaps." Software: practice and experience, 2015.
#Vallentin, Matthias, Vern Paxson, and Robin Sommer. "VAST: a unified platform for interactive network forensics." 13th USENIX Symposium on Networked Systems Design and Implementation (NSDI 16). 2016.
#Vallentin, Matthias. Scalable Network Forensics. Diss. University of California, Berkeley, 2016.

===inverted list===

#Culpepper, J. Shane, and Alistair Moffat. "Efficient set intersection for inverted indexing." ACM Transactions on Information Systems (TOIS), 2010.
#Schlegel, Benjamin, Thomas Willhalm, and Wolfgang Lehner. Fast Sorted-Set Intersection using SIMD Instructions, ADMS 2011.
#Inoue, Hiroshi, Moriyoshi Ohara, and Kenjiro Taura, Faster Set Intersection with SIMD instructions by Reducing Branch Mispredictions, VLDB 2014.
#Kane, Andrew, and Frank Wm Tompa, Skewed Partial Bitvectors for List Intersection, SIGIR 2014.

==大数据系统==
===Hadoop===

===Spark===

==机器智能==

===机器学习===

===深度学习===

=项目分组=

==第一组==
组长：

组员：

==第二组==
组长：王亦凡

组员：刘梦旸、邱昱田

==第三组==
组长：李子豪

组员：娄晨耀 张若天 邹逍遥

==第五组==
组长：

组员：

==第八组==
组长：熊铮

组员：范承泽，秦梓鑫

... ...

=论文研读=

要求：提交研读论文的PPT（正文部分不超过10页）。

时间：10月14日中午12点之前。

10月19日下午安排每组做一个小报告，每组时间不超过10分钟。


==第一组==
RUBIK: Efficient Threshold Queries on Massive Time Series, SSDBM 2015.

==第二组==
SciCSM: Novel Contrast Set Mining over Scientific Datasets Using Bitmap Indices, SSDBM 2015.

==第三组==
ALACRITY: Analytics-Driven Lossless Data Compression for Rapid In-Situ Indexing, Storing, and Querying, TLDKS X, 2013. 

==第四组==
VSEncoding: Efficient Coding and Fast Decoding of Integer Lists via Dynamic Programming, CIKM 2010.

==第五组==
Super-Scalar RAM-CPU Cache Compression, ICDE 2006.

==第六组==
Partitioned Elias-Fano Indexes, SIGIR 2014.

==第七组==
Fast Set Intersection through Run-Time Bitmap Construction over PForDelta-Compressed Indexes, Euro-Par 2014.

==第八组==
Optimal Space-time Tradeoffs for Inverted Indexes, WSDM 2015.

=课程项目=

==项目1-大数据==

===描述===
任务：基于位图索引的概念和原理，用C++实现一个位图索引数据库。


检验：完成对一段网流数据的索引建立，查询。在虚拟机上运行成功，得到正确结果。

 
网流数据：\\166.111.134.110\team-saturn\网流数据

 
代码托管：http://gitlab.icenter.tsinghua.edu.cn

 
时间：10月7日中午12点之前（特殊情况，推迟一周）

 
组织：以组为单位，要求要看到所有同学的贡献。

===作业提交===
====Group1==== 
[http://gitlab.icenter.tsinghua.edu.cn/xavieryao/bitmap-db  Group1]

====Group2==== 
[http://gitlab.icenter.tsinghua.edu.cn/bdmi_group2/bitmap  Group2]

====Group3==== 
[http://gitlab.icenter.tsinghua.edu.cn/3rd_group/bitmap_indexing  Group3]

====Group4==== 
[http://gitlab.icenter.tsinghua.edu.cn/taanng/Bitmap  Group4]

====Group5==== 
[http://gitlab.icenter.tsinghua.edu.cn/ddeerreekk/Experiment_1_Bitmap_Index  Group5]

====Group6==== 
[http://gitlab.icenter.tsinghua.edu.cn/group6/project1  Group6]

====Group7==== 
[http://gitlab.icenter.tsinghua.edu.cn/  Group7]

====Group8==== 
[http://gitlab.icenter.tsinghua.edu.cn/FQX/bitmap  Group8]

==项目2-机器智能==

===描述===

完成一个展示的智能系统

步骤1：设置azure虚拟机；

步骤2：架构flask-web服务；

步骤3：建立AI服务（Google Tensorflow）；

步骤4：lucida.ai；

步骤5：智能端开发（移动平台、嵌入式硬件）+thrift协议联调；


===作业提交===


====Group1====
[http://gitlab.icenter.tsinghua.edu.cn/  Group1]

====Group2==== 
[http://gitlab.icenter.tsinghua.edu.cn/  Group2]

====Group3==== 
[http://gitlab.icenter.tsinghua.edu.cn/  Group3]

====Group4==== 
[http://gitlab.icenter.tsinghua.edu.cn/  Group4]

====Group5==== 
[http://gitlab.icenter.tsinghua.edu.cn/  Group5]

====Group6==== 
[http://gitlab.icenter.tsinghua.edu.cn/  Group6]

====Group7==== 
[http://gitlab.icenter.tsinghua.edu.cn/  Group7]

====Group8==== 
[http://gitlab.icenter.tsinghua.edu.cn/  Group8]

=致谢=
本课程获得微软Azure云计算与机器学习捐赠支持。

=参考文献=
#Hennessy, John L., and David A. Patterson. Computer architecture: a quantitative approach. Elsevier, 2011.
#Matthew, Neil, and Richard Stones. Beginning linux programming. John Wiley & Sons, 2011.
#Stroustrup, Bjarne. The C++ programming language. Pearson Education, 2013.
#Weiss, Mark Allen. Data structures and algorithm analysis in Java. Addison-Wesley Longman Publishing Co., Inc., 1998.
#Flanagan, David. JavaScript: The definitive guide: Activate your web pages. " O'Reilly Media, Inc.", 2011.
#Grinberg, Miguel. Flask Web Development: Developing Web Applications with Python. O'Reilly Media, Inc., 2014.


#Yoshua Bengio, Ian Goodfellow, Aaron Courville, Deep Learning, MIT Press, 2016.
#Google brain team, TensorFlow: Large-scale machine learning on heterogeneous systems, whitepaper, 2015.
#Vijay Agneeswaran, Real-Time Applications with Storm, Spark, and More Hadoop Alternatives, 2014.