{"id":1117,"date":"2020-02-03T10:14:54","date_gmt":"2020-02-03T13:14:54","guid":{"rendered":"http:\/\/congresos.unlp.edu.ar\/xilapis?page_id=1117"},"modified":"2025-04-09T12:25:46","modified_gmt":"2025-04-09T15:25:46","slug":"software-catalogs","status":"publish","type":"page","link":"https:\/\/congresos.unlp.edu.ar\/xilapis\/software-catalogs\/","title":{"rendered":"Software\/Catalogs"},"content":{"rendered":"<h1>Software\/Catalogs<\/h1>\n<p>It is highly recommended that the participants have the following software\/catalogs installed\/downloaded in their laptops to be able to work in the hands-on sessions:<\/p>\n<p><strong>Python Libraries<\/strong><\/p>\n<div>python (3.8+)<\/div>\n<div><\/div>\n<div>\n<div>jupyter-notebook<\/div>\n<div>splusdata<\/div>\n<div>astroquery<\/div>\n<div>numpy<\/div>\n<div>astropy<\/div>\n<div>pandas<\/div>\n<div>scikit-learn<\/div>\n<div>matplotlib<\/div>\n<div>lsdb<\/div>\n<\/div>\n<div><\/div>\n<p><strong>Hands-on Notebooks<\/strong><\/p>\n<div><a href=\"https:\/\/drive.google.com\/file\/d\/1LBQo-2fMVb0u5MYxoEPSsfAa2b8XzC-l\/view?usp=sharing\">Application for stellar astronomy<\/a><\/div>\n<div><a href=\"https:\/\/drive.google.com\/file\/d\/1_Ic4xfXdI2eoy2zWjJaPXc8WgFMKUJXP\/view?usp=sharing\">Application for extragalactic astronomy_1<\/a><\/div>\n<div><a href=\"https:\/\/drive.google.com\/file\/d\/1-muEeUes8t5EDXrP0PDcyAxtwq-FXiiH\/view?usp=sharing\">Application for extragalactic astronomy_2<\/a><\/div>\n<div><a href=\"https:\/\/github.com\/Schwarzam\/XI-LAPIS-ML-astrocatalogs\">Machine learning applications with tabular data in Astronomy<\/a><\/div>\n<div><a href=\"https:\/\/drive.google.com\/file\/d\/19uAcGDPzyUg4jkC7ncOHdPfswCEhfqNo\/view?usp=sharing\">Deep learning applications with S-PLUS images<\/a><\/div>\n<div><a href=\"https:\/\/colab.research.google.com\/drive\/1Ap3a-pF0yc5cqMh0KEiIn_3xbWH9pA6h?usp=sharing\">Transients<\/a><\/div>\n<div><\/div>\n<p><strong>Datasets for Hands-on<\/strong><\/p>\n<div><a href=\"https:\/\/drive.google.com\/file\/d\/1qoBjlyXHZAtFiE1ChYCfsPN4IELiUyTm\/view?usp=sharing\">Deep learning applications with S-PLUS images dataset<\/a><\/div>\n<div><a href=\"https:\/\/drive.google.com\/file\/d\/17pQGoORbOYdd6H9bUbpi4NvdXnwx_3gp\/view?usp=sharing\">Transients<\/a><\/div>\n<div><a href=\"https:\/\/drive.google.com\/file\/d\/1fgjNhpEwJtucevaFid2-GVnK30wi-JP0\/view?usp=sharing\">Transients_small<\/a><\/div>\n","protected":false},"excerpt":{"rendered":"<p>Software\/Catalogs It is highly recommended that the participants have the following software\/catalogs installed\/downloaded in their laptops to be able to work in the hands-on sessions: Python Libraries python (3.8+) jupyter-notebook splusdata astroquery numpy astropy pandas scikit-learn matplotlib lsdb Hands-on Notebooks Application for stellar astronomy Application for extragalactic astronomy_1 Application for extragalactic astronomy_2 Machine learning applications [&hellip;]<\/p>\n","protected":false},"author":14,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"advgb_blocks_editor_width":"","advgb_blocks_columns_visual_guide":"","footnotes":""},"class_list":["post-1117","page","type-page","status-publish","hentry","post"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 4.9.8 - 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