PPT-Big Data, Stream Processing & Algorithms

Author : lindy-dunigan | Published Date : 2017-09-16

Supun Kamburugamuve For the PhD Qualifying Exam 12 19 2013 Advisory Committee Prof Geoffrey Fox Prof David Leake Prof Judy Qiu Outline Big Data Analytics

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Big Data, Stream Processing & Algorithms: Transcript

Supun Kamburugamuve For the PhD Qualifying Exam 12 19 2013 Advisory Committee Prof Geoffrey Fox Prof David Leake Prof Judy Qiu Outline Big Data Analytics Stack Stream Processing. Ion Stoica. UC Berkeley. BEARS. February 17, 2011. Big Data is Massive…. Facebook. : . 130TB/day: user logs. 200-400TB/day: 83 million pictures. Google: > 25 PB/day processed data. Data generated by LHC: 1 PB/sec. Amitabha. Roy. Ivo . Mihailovic. Willy . Zwaenepoel. 1. Graphs. 2. + . HyperANF. Pagerank. ALS. ….. Interesting information is encoded as graphs. Big Graphs. Large graphs are a subset of the big data . 1. Hetal. . Thakkar. , . Nikolay. Laptev, . Hamid. . Mousavi. , . Barzan. . Mozafari. , . Vincenzo. Russo, Carlo Zaniolo. . Computer Science Department UCLA. Data Stream Management Systems (DSMS). Lesson 1. Bernhard Pfahringer. University of Waikato, New Zealand. 2. Or:. Why . YOU. should care about Stream Mining. Overview. 3. Why is stream mining important?. How is it different from batch ML?. Antonio . Gomes. 31 August 2017. Outline. Disruptive. . Innovation. Competition. and . Regulation. Challenges. to . C. ompetition. Agencies. Big. Data. Algorithms. . and. . collusion. Competition. Distraction?. Mark Birkin. Professor of Spatial Analysis and Policy,. School of Geography, University of Leeds. Director, ESRC Consumer Data Research Centre. Director, Leeds Institute for Data Analytics. Pipelining. Instruction Pipeline. Pipeline Hazards and their solution. Array and Vector Processing. Pipelining and Vector Processing. Parallel Processing. It refers to techniques that are used to provide simultaneous data processing.. Lecture . 10: . Sublinear. Algorithm. Zhu Han. University of Houston. Thanks for Professor Dan Wang’s slides. 1. outline. Motivations. Inequalities and classifications . Examples. Applications. 2. Keynote. BigDat. 2015: International Winter School on Big Data. Tarragona, Spain, January 26-30, 2015. January 26 2015. Geoffrey . Fox . gcf@indiana.edu. . . http://www.infomall.org. School of Informatics and Computing. 10 Bat Algorithms Xin-She Yang, Nature-Inspired Optimization Algorithms, Elsevier, 2014 The bat algorithm (BA) is a bio-inspired algorithm developed by Xin-She Yang in 2010. 10.1 Echolocation of Bats Cynthia Lee. CS106B. Topics du Jour:. Last time:. Performance of Fibonacci recursive code. Look at growth of various functions. Traveling Salesperson problem. Problem sizes up to number of Facebook accounts. Lecture 17: Shortest Paths. Catie Baker. Spring . 2015. Announcements. Homework . 4 due next Wednesday, May . 13th. Spring 2015. 2. CSE373: Data Structures & Algorithms. Graph Traversals. For an arbitrary graph and a starting node . Lecture . 9: . Binary Heaps, Continued. Kevin Quinn. Fall . 2015. Fall 2015. 2. CSE373: Data Structures & Algorithms. Priority Queue ADT. Binary Heap. Fibonacci Heap. Paring. Heap. Binomial. Heap. Start Here--- https://bit.ly/41cD43F ---Get complete detail on 301B exam guide to crack F5 Certified Technology Specialist - Local Traffic Manager (F5-CTS LTM). You can collect all information on 301B tutorial, practice test, books, study material, exam questions, and syllabus. Firm your knowledge on F5 Certified Technology Specialist - Local Traffic Manager (F5-CTS LTM) and get ready to crack 301B certification. Explore all information on 301B exam with number of questions, passing percentage and time duration to complete test.

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