PPT-CSCI 6900: Mining Massive Datasets

Shannon Quinn with content graciously and viciously borrowed from William Cohens 10605 Machine Learning with Big Data and Stanfords MMDS MOOC httpwwwmmdsorg Big Data Astronomy. Itemset. Mining & Association Rules. Mining of Massive Datasets. Jure Leskovec, . Anand. . Rajaraman. , Jeff Ullman . Stanford University. http://www.mmds.org . Note to other teachers and users of these . Eileen Kraemer. August 24. th. , 2010. The University of Georgia. Java Threads & Concurrency, continued. Liveness. Deadlock. Starvation and . Livelock. Guarded Blocks. Immutable Objects. A Synchronized Class Example. Eileen Kraemer. August . 24. th. , 2010. The University of Georgia. Java Threads & . Concurrency, continued. Liveness. Deadlock. Starvation and . Livelock. Guarded Blocks. Immutable Objects. A Synchronized Class Example. Software. Eileen Kraemer. September 7th, . 2010. The University of Georgia. Outline. Review:. FSP and LTSA to represent concurrent processes (Ch.3). Structure diagrams (Ch. 3). UML and Java code for simple threaded programs (Ch. 3). (Part 1). Mining of Massive Datasets. Jure Leskovec, . Anand. . Rajaraman. , Jeff Ullman . Stanford University. http://www.mmds.org . Note to other teachers and users of these . slides:. We . would be delighted if you found this our material useful in giving your own lectures. Feel free to use these slides verbatim, or to modify them to fit your own needs. Jeffrey Miller, Ph.D.. http://www-scf.usc.edu/~csci201. USC CSCI 201L. Outline. USC CSCI 201L. 2. /25. CORBA. Program. CORBA Overview. The Common Object Request Broker Architecture (CORBA) is the Object Management Group’s (OMG) open, vendor-independent architecture and infrastructure that computer applications use to work together over networks. Jeffrey Miller, Ph.D.. jeffrey.miller@usc.edu. Outline. Conditions. Program. USC CSCI 201L. Conditional Statements. Java has three conditional statements, similar to C . if-else. switch-case. Conditional ternary operator . Jure Leskovec, . Anand. . Rajaraman. , Jeff Ullman . Stanford University. http://www.mmds.org . Note to other teachers and users of these . slides:. We . would be delighted if you found this our material useful in giving your own lectures. Feel free to use these slides verbatim, or to modify them to fit your own needs. CS246: Mining Massive Datasets. Jure Leskovec, . Stanford University. http://cs246.stanford.edu. Recap: Finding similar documents. Task:. . Given a large number (. N. in the millions or billions) of documents, find “near duplicates”. Overlapping Communities. Mining of Massive Datasets. Jure Leskovec, . Anand. . Rajaraman. , Jeff Ullman . Stanford University. http://www.mmds.org . Note to other teachers and users of these . slides:. Mining of Massive Datasets. Jure Leskovec, . Anand. . Rajaraman. , Jeff Ullman . Stanford University. http://www.mmds.org . Note to other teachers and users of these . slides:. We . would be delighted if you found this our material useful in giving your own lectures. Feel free to use these slides verbatim, or to modify them to fit your own needs. Frequent Itemset Mining & Association Rules Mining of Massive Datasets Jure Leskovec, Anand Rajaraman , Jeff Ullman Stanford University http://www.mmds.org Note to other teachers and users of these aspects and approaches. Fotis. E. . Psomopoulos. An EGI Virtual Team Project. As a field, bioinformatics relies heavily on public reference datasets and benefits from increasing compute capabilities to run algorithms. Bar-coding Cages. AR starting using barcodes for tracking census in December of 2005. Why bar-coding?. Provide timely census data. Provide accurate census data. Track room capacity. Each cage card/bar code is specific to the following information .