【Lecture 01】 CS246, Mining Massive Data Sets
Lecture 58 — Overview of Clustering | Mining of Massive Datasets | Stanford University
Lecture 39 — Sampling a Stream | Mining of Massive Datasets | Stanford University
Lecture 61 — The BFR Algorithm | Mining of Massive Datasets | Stanford University
Lecture 20 — Frequent Itemsets | Mining of Massive Datasets | Stanford University
Lecture 13 — Minhashing | Mining of Massive Datasets | Stanford University
Data Mining Explained | What is Data Mining?
Lecture 27 — Solving the BIGCLAM | Mining of Massive Datasets | Stanford University
Lecture 21 — A Priori Algorithm | Mining of Massive Datasets | Stanford University
4 13 Mining Data Streams 12 01
Lecture 38 — Bloom Filters | Mining of Massive Datasets | Stanford University
Data Mining with Weka (1.3: Exploring datasets)
Lecture 54 — Latent Factor Models | Stanford University
Lecture 1 — Distributed File Systems | Stanford University
Lecture 41 — Overview of Recommender Systems | Stanford University
Lecture 47 — Singular Value Decomposition | Stanford University
Lecture 42 — Content Based Recommendations | Stanford University
Lecture 43 — Collaborative Filtering | Stanford University
Lecture 29 — What Makes a Good Cluster (Advanced) | Stanford University
2 2 The MapReduce Computational Model 22 04
Filtering data stream - Mining Data Streams - Big Data Analytics
【Lecture 02】 CS246, Mining Massive Data Sets
6 2 Hierarchical Clustering 14 07
6 7 The AdWords Problem 19 21
Lecture 70 — Soft Margin SVMs | Mining of Massive Datasets | Stanford University
Lecture 59 — Hierarchical Clustering | Stanford University
Lecture 45 — Evaluating Recommender Systems | Stanford University
All Major Data Mining Techniques Explained With Examples
Lecture 65 — The Balance Algorithm | Mining of Massive Datasets | Stanford University
Data Mining Lecture 19: Mining social network graphs
Database Lesson #8 of 8 - Big Data, Data Warehouses, and Business Intelligence Systems
【Lecture 04】 CS246, Mining Massive Data Sets
2 3 Scheduling and Data Flow 12 43
WDM 1:What is Data Mining
Introduction to Process Mining: Turning (Big) Data into Real Value
Sampling from a Data Stream - Mining Data Stream - Big Data Analytics
6 6 Computational Advertising Bipartite Graph Matching 24 47
5 15 Latent Factor Recommender System 14 16
Big Data In 5 Minutes | What Is Big Data?| Big Data Analytics | Big Data Tutorial | Simplilearn
6 3 The k Means Algorithm 12 49
5 3 Collaborative Filtering 20 52
4 14 Counting 1 's 29 00 Advanced
10 Free Dataset Resources for Your Next Project!
2 4 Combiners and Partition Functions 12 17 Advanced
6 9 Generalized Balance 14 35 Advanced
Data Mining: How You're Revealing More Than You Think
Lecture 36 — Mining Data Streams | Mining of Massive Datasets | Stanford University
6 1 Overview of Clustering 8 46
6 4 The BFR Algorithm 25 01
2 1 Distributed File Systems 15 50
6 8 The Balance Algorithm 15 16
5 1 Overview of Recommender Systems 16 51
Lecture 46 — Dimensionality Reduction - Introduction | Stanford University
Lecture 93 — Spam Farms | Mining of Massive Datasets | Stanford University
Kim Pevey - A practical guide to analysis and interactive visualization of massive datasets
3 1 Finding Similar Sets 13 37
