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Web intelligence and big data

This course is about building 'web-intelligence' applications exploiting big data sources arising social media, mobile devices and sensors, using new big-data platforms based on the 'map-reduce' parallel programming paradigm. In the past, this course has been offered at the Indian Institute of Technology Delhi as well as . This course is about building `web-intelligence' applications exploiting big data sources arising social media, mobile devices and sensors, using new big-data platforms based on the 'map-reduce' parallel programming paradigm. The image cannot be displayed. Your computer may not have enough memory to open the image, or the image may have been corrupted. Restart your computer, and then open the file again. If the red x still appears, you may have to delete the image and then insert it again. The image cannot be displayed. Your computer.

GitHub is where people build software. More than 27 million people use GitHub to discover, fork, and contribute to over 80 million projects. lecture-videos/unit0-intro/Web Intelligence and Big Data Preamble (). mp4, MB. lecture-videos/unit0-intro/Web Intelligence and Big Data Revisiting Turing's Test ().mp4, MB. lecture-videos/unit0-intro/Web Intelligence and Big Data Web-Scale AI and Big Data ().mp4, MB. 2 Dec DECEMBER 02, Statement of Accomplishment KEYUR SHAH HAS COMPLETED Web Intelligence and Big Data This course is about building ' web-intelligen.

This course is about building 'web-intelligence' applications exploiting big data sources arising social media, mobile devices and sensors, using new big-data platforms based on the 'map-reduce' parallel programming paradigm. Course Description: The past decade has witnessed the successful of application of many AI techniques used at `web-scale', on what are popularly referred to as big data platforms based on the map-reduce parallel computing paradigm and associated technologies such as distributed file systems, no-SQL databases and . 4 Nov Web Intelligence and Big Data. (Spring ). Look. Big Data and Search; Indexing, PageRank and Memory. Listen. Information, Language and Classifiers; Analyzing Sentiment and Intent. Load. Big data technology, MapReduce; Databases and their evolution; Large scale Graph Databases. Learn.

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