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DTSTART;TZID=Europe/Helsinki:20180315T140000
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DTSTAMP:20180130T084431Z
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SUMMARY:Copil ISC-PIF
DESCRIPTION:
URL:https://iscpif.fr/evenements/copil-isc-pif-2/
LOCATION:ISC-PIF\, 113 rue Nationale\, Paris\, Paris\, 75013\, France
CATEGORIES:ISC-PIF Event,ISC-PIF Room 1.1,Private
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BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20180315T140000
DTEND;TZID=Europe/Helsinki:20180315T180000
DTSTAMP:20180405T094802Z
CREATED:20171127T095427Z
LAST-MODIFIED:20180405T094802Z
UID:22210-1521122400-1521136800@iscpif.fr
SUMMARY:JEDI – Multivac
DESCRIPTION:We’ve built a whole bunch of stuff to bring Data Science and Big Data hand to hand right to your doorstep.\n\n  \nIntroduction to Multivac Data Science Lab: \nWe have designed and implemented Hadoop cluster over more than 30 servers inside our private Cloud. This gives us Hadoop YARN and Hadoop HDFS to manage all resources with distributed storage over all those machines (highly available\, fault tolerance\, etc.). We have also implemented Apache Spark 2.2 on top of our Hadoop cluster.  \nIn addition\, we have configured and implemented two Web-based notebooks Apache Zeppelin and Hue that enable data-driven\, interactive data analytics\, and visualization. They also support multiple languages\, including Scala\, Spark SQL\, Python\, R\, Hive\, and Markdown. Apache Zeppelin and Hue also provide Apache Spark integration making it possible to take advantage of fast in-memory and distributed data processing engine to enhance your data science workflow.  \nWe believe this makes Big Data development and data science much easier for any research project dealing with large-scale data. \nWebsite: https://multivac.iscpif.fr \n  \nIn this training:\nPart I\n\nOverview of Multivac Platform\n\nArchitecture\nReal-time API engine\nData Science Lab\nProjects\n\n\nIntroduction to Apache Hadoop\nIntroduction to Apache Spark\n\nHands-on with Spark’s programming APIs (DataFrame/SQL\, Datasets\, RDD)\nOverview of Spark architecture: Core\, Streaming\, Standalone Mode\, DAG\n\n\nHow to work with interactive Spark Shell\nHow to submit jobs with Spark Submit\n\nIntellij\n\n\nIntroduction to « Interactive Spark Notebooks »\n\nApache Zeppelin\nHue UI / Notebooks\n\n\n\nPart II\n\nExploring Wikipedia Page Views\n\nComplex SQL on large-scale data (over 60 billion rows)\n\n\nIntroducing Standford CoreNLP with Spark\nIntroducing Spark NLP library\nMachine Learning by Spark\n\nFeature engineering\nML pipeline: string indexer\, vector assembler\, Random Forest Tree\, multi-class classification evaluator\, etc.\n\n\nUber: Trips Clustering\nBuilding a Movie Recommender\n\nASL algorithm and 100 million movie ratings from Netflix prize\n\n\n\nLevel of difficulty: \nIntermediate to advanced \nLanguage:\nThis training will be presented in English \nRequirement: \nLaptop/notebook (Linux or macOS preferably) \nChrome/Firefox/Safari browsers \nTraining by: \nMaziyar Panahi\, Big Data engineer and Cloud architect at ISC-PIF/CNRS \n  \n  \n 
URL:https://iscpif.fr/evenements/jedi-multivac-2/
LOCATION:ISC-PIF\, 113 rue Nationale\, Paris\, Paris\, 75013\, France
CATEGORIES:ISC-PIF Room 1.1,ISC-PIF Room 1.2
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