Mining Massive Datasets

About this Course

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.

Created by: Stanford University

Level: Advanced


Related Online Courses

L’expérience utilisateur se définit comme étant le résultat des états internes (ex. attentes, prédispositions) d’un utilisateur, des caractéristiques d’un système (ex. complexité, utilisabilité)... more
This course is a practical introduction to Istio, designed for anyone who wishes to build on their knowledge of Linux, Docker, and Kubernetes to learn how to install and configure a service mesh... more
Developed by Blockchain at Berkeley and faculty from UC Berkeley's premier Computer Science department, this course presents Bitcoin and cryptocurrencies as the motivation for blockchain... more
This course takes you through the first eight lessons of CS6750: Human-Computer Interaction as taught in the Georgia Tech Online Master of Science in Computer Science program. In this course,... more
The age of machine learning has arrived! Arm technology is powering a new generation of connected devices with sophisticated sensors that can collect a vast range of environmental, spatial and... more

CONTINUE SEARCH

FOLLOW COLLEGE PARENT CENTRAL