Natural language processing on computational cluster - NPFL118
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The aim of the course is to introduce methods required in natural language processing (processing huge data sets
in distributed environment and performing machine learning) and show how to effectively execute them on ÚFAL
computational Linux cluster. The course will cover ÚFAL network and cluster architecture, SGE (Sun/Oracle/Son of
Grid Engine), related Linux tools and best practices.
The whole course will be taught in several first weeks of the semester.
Last update: T_UFAL (04.05.2017)
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Solving the given assignments and active participation during the course.
To be able to meaningfully participate in the course and to complete the assignments, it is necessary to have access to the ÚFAL computational cluster. The course is therefore highly suitable for ÚFAL PhD students, but unsuitable for other students, apart from exceptional cases. Last update: Rosa Rudolf, Mgr., Ph.D. (26.09.2022)
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Data-Intensive Text Processing with MapReduce; Jimmy Lin and Chris Dyer.; Morgan & Claypool Publishers, 2010 Slurm - https://slurm.schedmd.com/ Apache Spark - https://spark.apache.org/ TensorFlow - https://www.tensorflow.org/ Last update: Popel Martin, Mgr., Ph.D. (01.10.2022)
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Technological difficulties with processing big data ÚFAL network and cluster architecture Slurm - architecture, commands Related Linux tools Last update: Popel Martin, Mgr., Ph.D. (01.10.2022)
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