YoVDO

Mining Massive Datasets

Offered By: Stanford University via edX

Tags

Data Mining Courses Machine Learning Courses Algorithms Courses MapReduce Courses Big Data Analytics Courses Clustering Courses Locality-Sensitive Hashing Courses Recommendation Systems Courses

Course Description

Overview

The course is based on the text Mining of Massive Datasets by Jure Leskovec, Anand Rajaraman, and Jeff Ullman, who by coincidence are also the instructors for the course.

The book is published by Cambridge Univ. Press, but by arrangement with the publisher, you can download a free copy Here. The material in this on-line course closely matches the content of the Stanford course CS246.

The major topics covered include: MapReduce systems and algorithms, Locality-sensitive hashing, Algorithms for data streams, PageRank and Web-link analysis, Frequent itemset analysis, Clustering, Computational advertising, Recommendation systems, Social-network graphs, Dimensionality reduction, and Machine-learning algorithms.


Taught by

Jure Leskovec, Anand Rajaraman, Jeff Ullman and

Tags

Related Courses

Building Features from Text Data
Pluralsight
Locality Sensitive Hashing for Search with Shingling + MinHashing - Python
James Briggs via YouTube
Private Nearest Neighbor Search with Sublinear Communication and Malicious Security
IEEE via YouTube
Time Signature Based Matching for Data Fusion and Coordination Detection in Cyber Relevant Logs
0xdade via YouTube
World's Hardest Jigsaw vs. Puzzle Machine - All White
Stuff Made Here via YouTube