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
En este curso introductorio de java aprenderás programación en Java de forma fácil e interactiva. Trabajarás con estructuras de datos fundamentales, tales como listas, pilas, colas y árboles, sobr... more
Quantum information is the foundation of the second quantum revolution. With classical computers and the classical internet, we are always manipulating classical information, made of bits. On the... more
Technology and computers are becoming more and more capable every day. Moving forward, computers will become increasingly good at solving problems. That means humans will become the problem finders... more
This is CS50x , Harvard University's introduction to the intellectual enterprises of computer science and the art of programming for majors and non-majors alike, with or without prior programming... more
IBM CICS is the trusted core of enterprise applications and transaction processing. You will experience writing, updating and running CICS applications as well as the new APIs, capabilities and... more