大数据技术(Big Data and Machine Learning)

（2018年春季学期–研究生专题课）

课程内容

• Hadoop, Spark

• 机器学习原理和算法

课程信息

时间：第3-14周；第5-7节课，每周二下午

地点：5-111

课程安排（有可能改变）

周期	日期	内容	幻灯片
3	3/20	Hadoop
4	3/27	Hadoop
5	4/3	Hadoop
6	4/10	Hadoop
7	4/17	ML
8	4/24	ML
10	5/8	ML
11	5/15	ML
12	5/22	ML
13	5/29	ML
14	6/5	ML

参考

• 这门课的内容可以关联 人工智能导论课 相关内容和参考链接。

• Theorem of the day

• K-Means clustering visualization

• Bigdata – Kmeans

• Big Data Analysis with Scala and Spark, on Coursera

• machine learning and data visualization

• Homepage of Kai Hwang

• http://www.kdnuggets.com/ （Data mining, Analitics, Big Data, Data Science）

• Seven steps machine learning with python

• Spark - decision trees for handwritten digit recognition

• Scala programming language website

• Scala center

• Shai Shalev-Shwartz

• Avrim Blum

• M. I. Jordan

• Nathan Srebro

• Ben Recht

• Jorge Nocedal

• Large-Scale Optimization for Data Science, Princeton

• Master M2 MVA: Convex Optimization, Algorithms and Applications

• A. Nemirovski

• Data8 - Foundations of Data Science

• CS294 RISE

• Ray - riselab

• CS231n convolutional neural networks course, Stanford

• CDMC 2017, cybersecurity data mining competition

开放数据

• CIFAR-10 dataset

https://github.com/caesar0301/awesome-public-datasets

http://archive.ics.uci.edu/ml/index.html

http://webscope.sandbox.yahoo.com/#datasets

相关文献

• 调研文献列表

以往课程网页

• 2017