{"id":4653,"date":"2023-09-18T15:21:54","date_gmt":"2023-09-18T13:21:54","guid":{"rendered":"https:\/\/www.hpc.mk\/?post_type=event_listing&#038;p=4653"},"modified":"2023-09-18T15:21:54","modified_gmt":"2023-09-18T13:21:54","slug":"julia-for-high-performance-data-analysis","status":"publish","type":"event_listing","link":"https:\/\/www.hpc.mk\/index.php\/event\/julia-for-high-performance-data-analysis\/","title":{"rendered":"Julia for High Performance Data Analysis"},"content":{"rendered":"\n<p>Julia is a modern high-level programming language that is fast (on par with traditional HPC languages like Fortran and C) and relatively easy to write like Python or Matlab. It thus solves the \u201ctwo-language problem\u201d, i.e. when prototype code in a high-level language needs to be combined with or rewritten in a lower-level language to improve performance.<\/p>\n\n\n\n<p>Although Julia is a general-purpose language, many of its features are particularly useful for numerical scientific computation, and a wide range of both domain-specific and general libraries are available for statistics, machine learning and numerical modelling.<\/p>\n\n\n\n<p>This online workshop will start by briefly covering the basics of Julia\u2019s syntax and features, and then introduce methods and libraries which are useful for writing high-performance code for modern HPC systems. After attending the workshop, you will:<\/p>\n\n\n\n<ul>\n<li>Be comfortable with Julia\u2019s syntax, in-built package manager, and development tools.<\/li>\n\n\n\n<li>Understand core language features like its type system, multiple dispatch, and composability.<\/li>\n\n\n\n<li>Be able to write your own Julia packages from scratch.<\/li>\n\n\n\n<li>Know how to perform various linear algebra analysis on datasets.<\/li>\n\n\n\n<li>Be productive in analysing and visualising large datasets in Julia using dataframes and visualisation packages.<\/li>\n\n\n\n<li>Be familiar with several Julia libraries for visualisation and machine learning.<\/li>\n\n\n\n<li>Understand how to analyse large datasets efficiently in Julia using statistical methods.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Prerequisites<\/h2>\n\n\n\n<ul>\n<li>Experience in one or more programming languages.<\/li>\n\n\n\n<li>Familiarity with basic concepts in linear algebra and machine learning.<\/li>\n\n\n\n<li>Basic experience with working in a terminal is also beneficial.&nbsp;<\/li>\n\n\n\n<li>Participants are expected to install Julia, VSCode and Zoom before the workshop starts<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Tentative agenda<\/h2>\n\n\n\n<p><strong>Day 1&nbsp;<\/strong><\/p>\n\n\n\n<p>Introduction to Julia syntax and features.<\/p>\n\n\n\n<p><strong>Day 2<\/strong><\/p>\n\n\n\n<p>Julia for data analysis, data frames, visualization, various data formats, read\/write data, missing data.<\/p>\n\n\n\n<p>Linear algebra, array matrix and vector operations, performance comparisons, random matrices, sparse matrices, eigenvalues\/eigenvectors and PCA.<\/p>\n\n\n\n<p><strong>Day 3<\/strong><\/p>\n\n\n\n<p>Clustering, classification, machine learning, deep learning.&nbsp;<\/p>\n\n\n\n<p><strong>Day 4<\/strong><\/p>\n\n\n\n<p>Regression, time series analysis and prediction.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Registration<\/h2>\n\n\n\n<p>Registrations are now closed.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Disclaimer<\/h2>\n\n\n\n<p><em>This training is intended for users established in the European Union or a country associated with&nbsp;Horizon&nbsp;2020. You can read more about the countries associated with Horizon2020 here&nbsp;<a href=\"https:\/\/ec.europa.eu\/info\/research-and-innovation\/statistics\/framework-programme-facts-and-figures\/horizon-2020-country-profiles_en\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/ec.europa.eu\/info\/research-and-innovation\/statistics\/framework-programme-facts-and-figures\/horizon-2020-country-profiles_e<\/a><\/em><\/p>\n","protected":false},"featured_media":4654,"template":"","meta":[],"event_listing_category":[],"event_listing_type":[],"_links":{"self":[{"href":"https:\/\/www.hpc.mk\/index.php\/wp-json\/wp\/v2\/event_listing\/4653"}],"collection":[{"href":"https:\/\/www.hpc.mk\/index.php\/wp-json\/wp\/v2\/event_listing"}],"about":[{"href":"https:\/\/www.hpc.mk\/index.php\/wp-json\/wp\/v2\/types\/event_listing"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.hpc.mk\/index.php\/wp-json\/wp\/v2\/media\/4654"}],"wp:attachment":[{"href":"https:\/\/www.hpc.mk\/index.php\/wp-json\/wp\/v2\/media?parent=4653"}],"wp:term":[{"taxonomy":"event_listing_category","embeddable":true,"href":"https:\/\/www.hpc.mk\/index.php\/wp-json\/wp\/v2\/event_listing_category?post=4653"},{"taxonomy":"event_listing_type","embeddable":true,"href":"https:\/\/www.hpc.mk\/index.php\/wp-json\/wp\/v2\/event_listing_type?post=4653"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}