斯坦福课程:海量数据挖掘(2019) by Jure Leskovec, Michele Catasta

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2020-03-29 23:30:16
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视频选集
(2/23)
1.Introduction; MapReduce and Spark
01:17:12
2.Frequent itemsets and Association rule
01:21:07
3.Locality-Sensitive Hashing
01:19:53
4.Theory of Locality-Sensitive Hashing
01:16:55
5.Clustering
01:19:15
6.Dimensionality Reduction SVD and CUR
01:19:47
7.Recommender Systems I
01:17:19
8.Recommender Systems II
01:18:25
9.PageRank
01:17:47
10.Link Spam and Introduction to Social
01:19:50
11.Community Detection in Graphs
01:19:10
12.Graph Representation Learning
01:19:26
13.Large-Scale Machine Learning I
01:23:09
14.Large-Scale Machine Learning II
01:20:10
15.Mining Data Streams I
01:17:48
16.Mining Data Streams II
01:22:36
17.Computational Advertising
01:21:29
18.Learning through Experimentation
01:20:29
19.Optimizing Submodular Functions
01:22:23
20.Final Review
01:11:37
21.Spark Tutorial
01:01:58
22.Proof Techniques + Probability Review
01:16:19
23.Linear Algebra Review
01:08:05

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