E78 Data Science with Daniel Slutsky

39:39
 
مشاركة
 

Manage episode 339628209 series 2968869
بواسطة ClojureStream Podcast and Jacek Schae، اكتشفه Player FM ومجتمعنا ـ حقوق الطبع والنشر مملوكة للناشر وليس لـPlayer FM، والصوت يبث مباشرة من خوادمه. اضغط زر الاشتراك لمتابعة التحديثات في Player FM، أو ألصق رابط التغذية الراجعة في أي تطبيق بودكاست آخر.
Daniel on Twitter - https://twitter.com/daslu_ Daniel on GitHub - https://github.com/daslu SciCloj - https://scicloj.github.io Study Group - https://scicloj.github.io/docs/community/groups/ processing tables: https://github.com/techascent/tech.ml.dataset github.com/scicloj/tablecloth processing arrays: https://github.com/cnuernber/dtype-next (should have mentioned) https://neanderthal.uncomplicate.org/ processing nested, unstructured data: https://github.com/clojure/core.match https://github.com/noprompt/meander https://github.com/redplanetlabs/specter math and stats: https://github.com/generateme/fastmath https://github.com/MastodonC/kixi.stats data viualization libraries: https://vega.github.io/ https://github.com/generateme/cljplot https://github.com/jsa-aerial/hanami classical machine learning: https://haifengl.github.io/ (wrapped in scicloj.ml) deep learning https://github.com/scicloj/clj-djl (wrapped in scicloj.ml) https://github.com/uncomplicate/deep-diamond machine learning workflows: https://github.com/scicloj/metamorph.ml the underlying pipeline notion: https://github.com/scicloj/metamorph wrapping all most of those machine learning libraries and workflow together: https://github.com/scicloj/scicloj.ml processing tables with spark: https://github.com/zero-one-group/geni should have mentioned: https://github.com/clj-python/libpython-clj https://github.com/scicloj/clojisr Video Courses: https://clojure.stream https://www.learnpedestal.com/ https://www.learndatomic.com/ https://www.learnreitit.com/ https://www.learnreagent.com/ https://www.learnreframe.com/ https://www.jacekschae.com/

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