{"id":39276,"date":"2019-10-31T22:29:10","date_gmt":"2019-10-31T19:29:10","guid":{"rendered":"https:\/\/prohoster.info\/blog\/proekt-open-data-hub-otkrytaya-platforma-mashinnogo-obucheniya-na-baze-red-hat-openshift\/"},"modified":"2019-10-31T22:29:10","modified_gmt":"2019-10-31T19:29:10","slug":"proekt-open-data-hub-otkrytaya-platforma-mashinnogo-obucheniya-na-baze-red-hat-openshift","status":"publish","type":"post","link":"https:\/\/prohoster.info\/sq\/blog\/administrirovanie\/proekt-open-data-hub-otkrytaya-platforma-mashinnogo-obucheniya-na-baze-red-hat-openshift","title":{"rendered":"Projekti Open Data Hub \u2013 nj\u00eb platform\u00eb e hapur p\u00ebr m\u00ebsim machine bazuar n\u00eb Red Hat OpenShift.","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p>E ardhmja ka ardhur, teknologjit\u00eb e inteligjenc\u00ebs artificiale dhe m\u00ebsimit t\u00eb makinave tashm\u00eb po p\u00ebrdoren me sukses nga dyqanet tuaja t\u00eb preferuara, kompanit\u00eb e transportit dhe madje edhe fermat q\u00eb rritin halvaret. <\/p>\n<p><img decoding=\"async\" alt=\"Projekti Open Data Hub \u2013 nj\u00eb platform\u00eb e hapur p\u00ebr m\u00ebsim machine bazuar n\u00eb Red Hat OpenShift.\" src=\"\/wp-content\/uploads\/2019\/10\/ac77ba2d00012d4f3bee803c9c26bc9f.jpg\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n <br \/>\nDhe n\u00ebse di\u00e7ka ekziston, at\u00ebher\u00eb do t\u00eb ket\u00eb informacion p\u00ebr t\u00eb\u2026 nj\u00eb projekt t\u00eb hapur! Shihni si Open Data Hub ndihmon n\u00eb shkall\u00ebzimin e teknologjive t\u00eb reja dhe shmangien e v\u00ebshtir\u00ebsive gjat\u00eb implementimit t\u00eb tyre.<br \/>\n<noindex><a rel=\"nofollow\" name=\"habracut\"><\/a><\/noindex><br \/>\nP\u00ebr t\u00eb gjitha p\u00ebrfitimet e inteligjenc\u00ebs artificiale (artificial Intelligence, AI) dhe m\u00ebsimit t\u00eb makinave (machine learning, ML), organizatat shpesh hasin v\u00ebshtir\u00ebsi n\u00eb shkall\u00ebzimin e k\u00ebtyre teknologjive. Problemet kryesore zakonisht jan\u00eb si m\u00eb posht\u00eb:<\/p>\n<ul>\n<li><b>Shk\u00ebmbimi i informacionit dhe bashk\u00ebpunimi<\/b> \u2013 \u00ebsht\u00eb praktikisht e pamundur t\u00eb shk\u00ebmbehet informacion pa mundime dhe t\u00eb bashk\u00ebpunoni n\u00eb m\u00ebnyr\u00eb t\u00eb shpejt\u00eb.<\/li>\n<li><b>Qasja n\u00eb t\u00eb dh\u00ebna<\/b> \u2013 p\u00ebr \u00e7do detyr\u00eb duhet t\u00eb nd\u00ebrtohet nga fillimi dhe manualisht, q\u00eb merr shum\u00eb koh\u00eb.<\/li>\n<li><b>Qasja sipas k\u00ebrkes\u00ebs<\/b> \u2013 nuk ka mund\u00ebsi p\u00ebr t\u00eb marr\u00eb qasje on-demand n\u00eb mjetet dhe platform\u00ebn e m\u00ebsimit t\u00eb makinave, si dhe n\u00eb infrastruktur\u00ebn llogarit\u00ebse.<\/li>\n<li><b>Prodhimi<\/b> \u2013 modelet mbeten n\u00eb faz\u00ebn e prototipit dhe nuk arrijn\u00eb n\u00eb prodhimin masiv.<\/li>\n<li><b>Gjetja dhe shpjegimi i rezultateve t\u00eb AI<\/b> \u2013 riprodhueshm\u00ebria, ndjekja dhe shpjegimi i rezultateve t\u00eb AI\/ML jan\u00eb t\u00eb v\u00ebshtira.<\/li>\n<\/ul>\n<p>\nN\u00ebse k\u00ebto probleme lihen t\u00eb patrajtuara, ato ndikojn\u00eb negativisht n\u00eb shpejt\u00ebsin\u00eb, efikasitetin dhe produktivitetin e specialist\u00ebve t\u00eb vlefsh\u00ebm t\u00eb t\u00eb dh\u00ebnave dhe analiz\u00ebs. Kjo \u00e7on n\u00eb frustrim, zhg\u00ebnjim n\u00eb pun\u00eb, dhe p\u00ebrfundimisht presionet e biznesit ndaj AI\/ML shkojn\u00eb n\u00eb rrug\u00eb t\u00eb gabuar.<\/p>\n<p>P\u00ebrgjegj\u00ebsia p\u00ebr zgjidhjen e k\u00ebtyre problemeve i takon specialist\u00ebve t\u00eb IT-s\u00eb, t\u00eb cil\u00ebt duhet t\u00eb ofrojn\u00eb analist\u00ebve t\u00eb t\u00eb dh\u00ebnave \u2013 sakt\u00ebsisht, di\u00e7ka si nj\u00eb cloud. N\u00ebse d\u00ebshirohet m\u00eb n\u00eb detaje, nevojitet nj\u00eb platform\u00eb q\u00eb ofron lirin\u00eb e zgjedhjes dhe ka akses t\u00eb thjesht\u00eb dhe t\u00eb leht\u00eb. Ajo duhet t\u00eb jet\u00eb e shpejt\u00eb, duhet t\u00eb rregullohet leht\u00ebsisht, t\u00eb shkall\u00ebzohet sipas k\u00ebrkes\u00ebs dhe t\u00eb jet\u00eb rezistente ndaj d\u00ebshtimeve. Nd\u00ebrtimi i nj\u00eb platforme t\u00eb till\u00eb mbi teknologji me kod t\u00eb hapur ndihmon n\u00eb shmangien e var\u00ebsis\u00eb nga shit\u00ebsit dhe ruan nj\u00eb avantazh strategjik afatgjat\u00eb n\u00eb kontrollin e kostove.<\/p>\n<p>Para disa vjet\u00ebsh, di\u00e7ka e ngjashme ndodhte n\u00eb zhvillimin e aplikacioneve, duke \u00e7uar n\u00eb lindjen e mikrosh\u00ebrbimeve, mjediseve hibride t\u00eb cloud-it, automatizimit IT dhe proceseve agile. P\u00ebr t\u00eb p\u00ebrballuar t\u00eb gjitha k\u00ebto, profesionist\u00ebt IT filluan t\u00eb p\u00ebrdorin kontejner\u00eb, Kubernetes dhe cloud-e hibride t\u00eb hapura.<\/p>\n<p>Tani kjo p\u00ebrvoj\u00eb aplikohet p\u00ebr t\u00eb p\u00ebrballuar sfidat e AI. Prandaj, profesionist\u00ebt IT krijojn\u00eb platforma q\u00eb mb\u00ebshteten n\u00eb kontejner\u00eb, lejojn\u00eb krijimin e sh\u00ebrbimeve AI\/ML brenda proceseve agile, p\u00ebrshpejtojn\u00eb inovacionet dhe nd\u00ebrtohen me fokus n\u00eb cloud-in hibrid.<\/p>\n<p><img decoding=\"async\" alt=\"Projekti Open Data Hub \u2013 nj\u00eb platform\u00eb e hapur p\u00ebr m\u00ebsim machine bazuar n\u00eb Red Hat OpenShift.\" src=\"\/wp-content\/uploads\/2019\/10\/a899093183092edd8b2902f47b0495a8.jpg\" style=\"display:block;margin: 0 auto;\" \/><\/p>\n<p>Nd\u00ebrtimin e nj\u00eb platforme t\u00eb till\u00eb do ta fillojm\u00eb me Red Hat OpenShift, platform\u00ebn ton\u00eb t\u00eb kontejner\u00ebve Kubernetes p\u00ebr cloud-in hibrid, e cila ka nj\u00eb ekosistem n\u00eb rritje t\u00eb zgjidhjeve softuerike dhe harduerike ML (NVIDIA, H2O.ai, Starburst, PerceptiLabs, etj.). Disa nga klient\u00ebt e Red Hat, si BMW Group, ExxonMobil dhe t\u00eb tjer\u00eb, tashm\u00eb kan\u00eb zbatuar zinxhir\u00eb kontejner\u00ebzish t\u00eb mjeteve ML dhe proceseve DevOps mbi k\u00ebt\u00eb platform\u00eb dhe ekosistemin e saj, p\u00ebr t\u00eb \u00e7uar arkitektur\u00ebn e tyre ML n\u00eb nj\u00eb status industrial dhe p\u00ebr t\u00eb p\u00ebrshpejtuar pun\u00ebn e analist\u00ebve t\u00eb t\u00eb dh\u00ebnave.<\/p>\n<p>Nj\u00eb arsye tjet\u00ebr pse ne filluam projektin Open Data Hub \u00ebsht\u00eb t\u00eb tregojm\u00eb nj\u00eb shembull t\u00eb arkitektur\u00ebs mbi disa projekte t\u00eb hapura dhe t\u00eb shfaqim se si mund t\u00eb realizohet e gjith\u00eb cikli i zgjidhjes ML mbi platform\u00ebn OpenShift.<\/p>\n<h3>Projekti Open Data Hub<\/h3>\n<p>\nKy \u00ebsht\u00eb nj\u00eb projekt me kod t\u00eb hapur, i cili zhvillohet n\u00eb kuad\u00ebr t\u00eb komunitetit p\u00ebrkat\u00ebs t\u00eb zhvillimit dhe realizon ciklin e plot\u00eb t\u00eb operacioneve \u2013 nga ngarkimi dhe transformimi i t\u00eb dh\u00ebnave fillestare deri te formimi, trajnimi dhe mb\u00ebshtetja e modelit \u2013 duke zgjidhur \u00e7\u00ebshtjet AI\/ML me ndihm\u00ebn e kontejner\u00ebve dhe Kubernetes n\u00eb platform\u00ebn OpenShift. Ky projekt mund t\u00eb shqyrtohet si nj\u00eb implementim referenc\u00eb, nj\u00eb shembull se si t\u00eb krijohet nj\u00eb zgjidhje t\u00eb hapur t\u00eb klas\u00ebs \"AI\/ML si sh\u00ebrbim\" mbi baz\u00ebn e OpenShift dhe mjeteve p\u00ebrkat\u00ebse me kod t\u00eb hapur, si Tensorflow, JupyterHub, Spark dhe t\u00eb tjer\u00eb. \u00cbsht\u00eb e r\u00ebnd\u00ebsishme t\u00eb theksohet se Red Hat e p\u00ebrdor k\u00ebt\u00eb projekt p\u00ebr ofrimin e sh\u00ebrbimeve t\u00eb saj AI\/ML. P\u00ebr m\u00eb tep\u00ebr, OpenShift integrohet me zgjidhjet kryesore softuerike dhe harduerike ML nga NVIDIA, Seldon, Starbust dhe t\u00eb tjer\u00eb ofrues, duke leht\u00ebsuar nd\u00ebrtimin dhe lan\u00e7imin e sistemeve t\u00eb veta t\u00eb m\u00ebsimit t\u00eb makinave.<\/p>\n<p><img decoding=\"async\" alt=\"Projekti Open Data Hub \u2013 nj\u00eb platform\u00eb e hapur p\u00ebr m\u00ebsim machine bazuar n\u00eb Red Hat OpenShift.\" src=\"\/wp-content\/uploads\/2019\/10\/85a4266250e1afca62bdc9406422510c.jpg\" style=\"display:block;margin: 0 auto;\" \/><\/p>\n<p>Projekti Open Data Hub \u00ebsht\u00eb i orientuar drejt kategorive t\u00eb m\u00ebposhtme t\u00eb p\u00ebrdoruesve dhe skenar\u00ebve t\u00eb p\u00ebrdorimit:<\/p>\n<ul>\n<li>Analisti i t\u00eb dh\u00ebnave, i cili ka nevoj\u00eb p\u00ebr nj\u00eb zgjidhje p\u00ebr realizimin e projekteve ML, t\u00eb organizuar n\u00eb nj\u00eb model cloud me funksione vet\u00eb-sh\u00ebrbimi.<\/li>\n<li>Analisti i t\u00eb dh\u00ebnave, i cili ka nevoj\u00eb p\u00ebr zgjedhje maksimale nga e gjith\u00eb larmia e instrumenteve dhe platformave t\u00eb fundit AI\/ML me kod t\u00eb hapur.<\/li>\n<li>Analisti i t\u00eb dh\u00ebnave, i cili ka nevoj\u00eb p\u00ebr qasje n\u00eb burimet e t\u00eb dh\u00ebnave gjat\u00eb trajnimet e modeleve.<\/li>\n<li>Analisti i t\u00eb dh\u00ebnave, i cili ka nevoj\u00eb p\u00ebr qasje n\u00eb resurset kompjuterike (CPU, GPU, memorie).<\/li>\n<li>Analisti i t\u00eb dh\u00ebnave, i cili k\u00ebrkon mund\u00ebsin\u00eb p\u00ebr t\u00eb bashk\u00ebpunuar dhe shk\u00ebmbyer rezultatet e pun\u00ebs me koleg\u00ebt, p\u00ebr t\u00eb marr\u00eb feedback dhe p\u00ebr t\u00eb sjell\u00eb p\u00ebrmir\u00ebsime p\u00ebrmes iteracioneve t\u00eb shpejta.<\/li>\n<li>Analisti i t\u00eb dh\u00ebnave, i cili d\u00ebshiron t\u00eb bashk\u00ebveproj\u00eb me zhvilluesit (dhe ekipet devops), p\u00ebr t'i \u00e7uar modelet dhe rezultatet e tij t\u00eb ML n\u00eb prodhim.<\/li>\n<li>Inxhinieri i t\u00eb dh\u00ebnave, i cili ka nevoj\u00eb t'i jap\u00eb analistit t\u00eb t\u00eb dh\u00ebnave qasje n\u00eb burime t\u00eb ndryshme t\u00eb t\u00eb dh\u00ebnave duke e respektuar standardet dhe k\u00ebrkesat e siguris\u00eb.<\/li>\n<li>Administrator\/operator i sistemeve IT, i cili ka nevoj\u00eb p\u00ebr mund\u00ebsin\u00eb p\u00ebr t\u00eb kontrolluar pa ndonj\u00eb p\u00ebrpjekje t\u00eb tep\u00ebrt ciklin e jet\u00ebs (instalimi, konfigurimi, p\u00ebrdit\u00ebsimi) t\u00eb komponent\u00ebve dhe teknologjive me kod t\u00eb hapur. Po ashtu, i duhen instrumente p\u00ebr menaxhim dhe kuotim p\u00ebrkat\u00ebs.<\/li>\n<\/ul>\n<p>\nProjekti Open Data Hub bashkon nj\u00eb gam\u00eb t\u00eb gjer\u00eb mjetesh me kod t\u00eb hapur p\u00ebr realizimin e ciklit t\u00eb plot\u00eb t\u00eb operacioneve AI\/ML. Si mjeti kryesor i pun\u00ebs p\u00ebr analistin e t\u00eb dh\u00ebnave k\u00ebtu p\u00ebrdoret Jupyter Notebook. Ky instrument sot g\u00ebzon nj\u00eb popullaritet t\u00eb gjer\u00eb mes specialist\u00ebve t\u00eb p\u00ebrpunimit dhe analiz\u00ebs s\u00eb t\u00eb dh\u00ebnave, dhe Open Data Hub u mund\u00ebson atyre t\u00eb krijojn\u00eb dhe menaxhojn\u00eb leht\u00ebsisht hap\u00ebsira pune Jupyter Notebook, duke p\u00ebrdorur JupyterHub t\u00eb vendosur brenda. P\u00ebrve\u00e7 krijimit dhe importimit t\u00eb notebooks Jupyter, projekti Open Data Hub gjithashtu p\u00ebrmban nj\u00eb seri notebooks t\u00eb gatshme n\u00eb form\u00eb t\u00eb bibliotek\u00ebs AI Library.<\/p>\n<p>Kyta biblioteka \u00ebsht\u00eb nj\u00eb koleksion komponent\u00ebsh open-source t\u00eb m\u00ebsimit t\u00eb makinerive dhe zgjidhjeve p\u00ebr skenar\u00eb t\u00eb zakonsh\u00ebm, duke e thjeshtuar prototipizimin e shpejt\u00eb. JupyterHub integrohet me modelin e qasjes RBAC t\u00eb OpenShift, \u00e7ka lejon p\u00ebrdorimin e llogarive ekzistuese t\u00eb OpenShift dhe implementimin e nj\u00eb hyrjeje t\u00eb vetme n\u00eb sistem. P\u00ebr m\u00eb tep\u00ebr, JupyterHub ofron nj\u00eb nd\u00ebrfaqe p\u00ebrdoruesi t\u00eb quajtur spawner, me an\u00eb t\u00eb s\u00eb cil\u00ebs p\u00ebrdoruesi mund t\u00eb konfiguroj\u00eb leht\u00ebsisht sasin\u00eb e burimeve kompjuterike (nuk dhe procesor\u00eb, memorie, GPU) p\u00ebr Notebook-un e zgjedhur Jupyter.<\/p>\n<p>Pasi analisti i t\u00eb dh\u00ebnave t\u00eb ket\u00eb krijuar dhe konfiguruar notebook-un, t\u00eb gjitha shqet\u00ebsimet e tjera p\u00ebr t\u00eb mbulohen nga planifikuesi Kubernetes, i cili \u00ebsht\u00eb pjes\u00eb e OpenShift. P\u00ebrdoruesit duhet vet\u00ebm t\u00eb kryejn\u00eb eksperimentet e tyre, t\u00eb ruajn\u00eb dhe t\u00eb ndajn\u00eb rezultatet e pun\u00ebs s\u00eb tyre. P\u00ebr m\u00eb tep\u00ebr, p\u00ebrdoruesit e avancuar mund t\u00eb aksesojn\u00eb drejtp\u00ebrdrejt shell-in CLI t\u00eb OpenShift nga Jupyter notebooks, p\u00ebr t\u00eb angazhuar primitive t\u00eb Kubernetes, si\u00e7 \u00ebsht\u00eb Job, ose funksionalitetin e OpenShift, si Tekton apo Knative. Ose p\u00ebr k\u00ebt\u00eb, mund t\u00eb p\u00ebrdorin GUI-n\u00eb e p\u00ebrdoruesit t\u00eb OpenShift t\u00eb quajtur \"web-console OpenShift.\"<\/p>\n<p><img decoding=\"async\" alt=\"Projekti Open Data Hub \u2013 nj\u00eb platform\u00eb e hapur p\u00ebr m\u00ebsim machine bazuar n\u00eb Red Hat OpenShift.\" src=\"\/wp-content\/uploads\/2019\/10\/601d63af1467b01df504954416effb3d.jpg\" style=\"display:block;margin: 0 auto;\" \/><\/p>\n<p><img decoding=\"async\" alt=\"Projekti Open Data Hub \u2013 nj\u00eb platform\u00eb e hapur p\u00ebr m\u00ebsim machine bazuar n\u00eb Red Hat OpenShift.\" src=\"\/wp-content\/uploads\/2019\/10\/4647d8d979cc26b0c20cd3d63caed501.jpg\" style=\"display:block;margin: 0 auto;\" \/><\/p>\n<p>Duke kaluar n\u00eb faz\u00ebn e ardhshme, Open Data Hub ofron mund\u00ebsin\u00eb p\u00ebr t\u00eb menaxhuar konveyor\u00ebt e t\u00eb dh\u00ebnave (data pipelines). P\u00ebr k\u00ebt\u00eb p\u00ebrdoret objekti Ceph, i cili ofrohet si nj\u00eb depo e dh\u00ebnash p\u00ebrmbush\u00ebse S3. Apache Spark siguron transmetimin e t\u00eb dh\u00ebnave nga burime t\u00eb jashtme ose depoja e brendshme Ceph S3, si dhe lejon kryerjen e transformimeve t\u00eb parakohshme t\u00eb t\u00eb dh\u00ebnave. Apache Kafka ofron menaxhim t\u00eb avancuar p\u00ebr konveyor\u00ebt e t\u00eb dh\u00ebnave (ku mund t\u00eb kryhen ngarkesa t\u00eb shumta, si dhe operacione transformimi, analize dhe ruajtjeje t\u00eb t\u00eb dh\u00ebnave).<\/p>\n<p>Pra, analisti i t\u00eb dh\u00ebnave ka akses n\u00eb t\u00eb dh\u00ebna dhe ka nd\u00ebrtuar nj\u00eb model. Tani ai d\u00ebshiron t\u00eb ndaj\u00eb rezultatet e marra me koleg\u00ebt ose zhvilluesit e aplikacioneve, duke iu ofruar atyre modelin e tij mbi parimin e sh\u00ebrbimit. P\u00ebr k\u00ebt\u00eb, nevojitet nj\u00eb server ndihm\u00ebs, dhe Open Data Hub ka nj\u00eb server t\u00eb till\u00eb, t\u00eb quajtur Seldon, i cili lejon publikimin e modelit si nj\u00eb sh\u00ebrbim RESTful.<\/p>\n<p>N\u00eb nj\u00eb moment, n\u00eb serverin Seldon, k\u00ebto modele b\u00ebhen disa, dhe lind nevoja p\u00ebr monitorimin e p\u00ebrdorimit t\u00eb tyre. P\u00ebr k\u00ebt\u00eb, Open Data Hub ofron nj\u00eb koleksion t\u00eb metrikave p\u00ebrkat\u00ebse dhe nj\u00eb motor raportimi t\u00eb bazuar n\u00eb mjete t\u00eb njohura monitorimi me kod t\u00eb hapur si Prometheus dhe Grafana. Si rezultat, ne marrim feedback p\u00ebr monitorimin e p\u00ebrdorimit t\u00eb modeleve AI, ve\u00e7an\u00ebrisht n\u00eb ambientin e prodhimit.<\/p>\n<p><img decoding=\"async\" alt=\"Projekti Open Data Hub \u2013 nj\u00eb platform\u00eb e hapur p\u00ebr m\u00ebsim machine bazuar n\u00eb Red Hat OpenShift.\" src=\"\/wp-content\/uploads\/2019\/10\/1c95bcd2656ea8376ccc0a91fa266897.jpg\" style=\"display:block;margin: 0 auto;\" \/><\/p>\n<p>K\u00ebshtu, Open Data Hub siguron nj\u00eb qasje si n\u00eb re gjat\u00eb t\u00ebr\u00eb ciklit t\u00eb operacioneve AI\/ML, duke filluar nga qasja dhe p\u00ebrgatitja e t\u00eb dh\u00ebnave dhe duke p\u00ebrfunduar me trajnim dhe k\u00ebrcimin e modelit n\u00eb prodhim.<\/p>\n<h3>Mblidhni gjith\u00e7ka s\u00eb bashku<\/h3>\n<p>\nTani lind pyetja se si t\u00eb organizohet t\u00ebr\u00eb kjo nga administratori i OpenShift. Dhe k\u00ebtu hyn n\u00eb p\u00ebrdorim nj\u00eb operator i ve\u00e7ant\u00eb Kubernetes p\u00ebr projektet Open Data Hub.<\/p>\n<p><img decoding=\"async\" alt=\"Projekti Open Data Hub \u2013 nj\u00eb platform\u00eb e hapur p\u00ebr m\u00ebsim machine bazuar n\u00eb Red Hat OpenShift.\" src=\"\/wp-content\/uploads\/2019\/10\/4bcb406f6886227ef357cd0318767ca2.jpg\" style=\"display:block;margin: 0 auto;\" \/><\/p>\n<p>Ky operator menaxhon instalimin, konfigurimin dhe ciklin e jet\u00ebs s\u00eb projektit Open Data Hub, duke p\u00ebrfshir\u00eb depolimin e mjeteve t\u00eb lartp\u00ebrmendura si JupyterHub, Ceph, Spark, Kafka, Seldon, Prometheus dhe Grafana. Projekti Open Data Hub mund t\u00eb gjendet n\u00eb konsol\u00ebn e webit t\u00eb OpenShift, n\u00eb seksionin e operator\u00ebve komunitar\u00eb. N\u00eb k\u00ebt\u00eb m\u00ebnyr\u00eb, administratori i OpenShift mund t\u00eb p\u00ebrcaktoj\u00eb se projektet p\u00ebrkat\u00ebse t\u00eb OpenShift p\u00ebrfshihen n\u00eb kategorin\u00eb \"projekti Open Data Hub\". Kjo b\u00ebhet nj\u00eb her\u00eb. Pas k\u00ebsaj, analisti i t\u00eb dh\u00ebnave kalon p\u00ebrmes konsol\u00ebs s\u00eb webit t\u00eb OpenShift n\u00eb hap\u00ebsir\u00ebn e tij t\u00eb projekteve dhe sheh se p\u00ebr projektet e tij \u00ebsht\u00eb instaluar dhe n\u00eb dispozicion operatori p\u00ebrkat\u00ebs Kubernetes. Pastaj ai krijon nj\u00eb instanc\u00eb t\u00eb projektit Open Data Hub me nj\u00eb klik t\u00eb vet\u00ebm dhe menj\u00ebher\u00eb merr qasje n\u00eb mjetet e p\u00ebrmendura m\u00eb par\u00eb. Dhe gjith\u00eb kjo mund t\u00eb konfigurohet n\u00eb nj\u00eb mod t\u00eb lart\u00eb t\u00eb disponueshm\u00ebris\u00eb dhe q\u00ebndrueshm\u00ebris\u00eb.<\/p>\n<p><img decoding=\"async\" alt=\"Projekti Open Data Hub \u2013 nj\u00eb platform\u00eb e hapur p\u00ebr m\u00ebsim machine bazuar n\u00eb Red Hat OpenShift.\" src=\"\/wp-content\/uploads\/2019\/10\/811a85229d0f3e54a96de1adb9aaeb24.jpg\" style=\"display:block;margin: 0 auto;\" \/><\/p>\n<p>N\u00ebse d\u00ebshiron ta provosh projektin Open Data Hub me duar, fillo me <noindex><a rel=\"nofollow\" href=\"https:\/\/opendatahub.io\/docs\/getting-started\/quick-installation.html\">udh\u00ebzimet e instalimit dhe tutorialin hyr\u00ebs<\/a><\/noindex>. Detajet teknike t\u00eb arkitektur\u00ebs s\u00eb Open Data Hub mund t\u00eb gjenden <noindex><a rel=\"nofollow\" href=\"https:\/\/opendatahub.io\/docs\/architecture.html\">k\u00ebtu<\/a><\/noindex>, planet p\u00ebr zhvillimin e projektit \u2013 <noindex><a rel=\"nofollow\" href=\"https:\/\/opendatahub.io\/docs\/roadmap\/future.html\">k\u00ebtu<\/a><\/noindex>. N\u00eb t\u00eb ardhmen, planifikohet t\u00eb realizohet nj\u00eb integrim shtes\u00eb me Kubeflow, t\u00eb zgjidhen disa \u00e7\u00ebshtje rregullative dhe sigurie, si dhe t\u00eb organizohet integrimi me sistemet e bazuara n\u00eb rregulla Drools dhe Optaplanner. T\u00eb shpreh\u00ebsh mendimin t\u00ebnd dhe t\u00eb b\u00ebhesh pjes\u00eb e projektit <noindex><a rel=\"nofollow\" href=\"https:\/\/opendatahub.io\/docs\/additional.html#community\">Open Data Hub<\/a><\/noindex> mund t\u00eb b\u00ebhet n\u00eb faqen <noindex><a rel=\"nofollow\" href=\"https:\/\/opendatahub.io\/docs\/additional.html#community\">e komunitetit<\/a><\/noindex>. <\/p>\n<p>N\u00eb p\u00ebrmbledhje: problemet serioze me shkall\u00ebzimin pengojn\u00eb organizatat t\u00eb realizojn\u00eb plot\u00ebsisht potencialin e inteligjenc\u00ebs artificiale dhe m\u00ebsimit automat. Red Hat OpenShift \u00ebsht\u00eb p\u00ebrdorur prej koh\u00ebsh me sukses p\u00ebr t\u00eb zgjidhur probleme t\u00eb ngjashme n\u00eb industrin\u00eb e softuerit. Projekti Open Data Hub, i realizuar n\u00eb kuad\u00ebr t\u00eb komunitetit zhvillues me kod t\u00eb hapur, ofron nj\u00eb arkitektur\u00eb standarde p\u00ebr organizimin e ciklit t\u00eb plot\u00eb t\u00eb operacioneve AI\/ML mbi baz\u00ebn e Cloud-it hibrid OpenShift. Ne kemi nj\u00eb plan t\u00eb qart\u00eb dhe t\u00eb menduar p\u00ebr zhvillimin e k\u00ebtij projekti dhe jemi t\u00eb vendosur p\u00ebr t\u00eb krijuar rreth tij nj\u00eb komunitet aktiv dhe produktiv zhvilluesish t\u00eb zgjidhjeve AI me kod t\u00eb hapur n\u00eb platform\u00ebn OpenShift.<br \/>\n<br \/>Burimi: <a content=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/company\/redhatrussia\/blog\/472836\/\">habr.com<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>\u0411\u0443\u0434\u0443\u0449\u0435\u0435 \u043d\u0430\u0441\u0442\u0443\u043f\u0438\u043b\u043e, \u0442\u0435\u0445\u043d\u043e\u043b\u043e\u0433\u0438\u0438 \u0438\u0441\u043a\u0443\u0441\u0441\u0442\u0432\u0435\u043d\u043d\u043e\u0433\u043e \u0438\u043d\u0442\u0435\u043b\u043b\u0435\u043a\u0442\u0430 \u0438 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f \u0443\u0436\u0435 \u0443\u0441\u043f\u0435\u0448\u043d\u043e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u044e\u0442 \u0432\u0430\u0448\u0438 \u043b\u044e\u0431\u0438\u043c\u044b\u0435 \u043c\u0430\u0433\u0430\u0437\u0438\u043d\u044b, \u0442\u0440\u0430\u043d\u0441\u043f\u043e\u0440\u0442\u043d\u044b\u0435 \u043a\u043e\u043c\u043f\u0430\u043d\u0438\u0438 \u0438 \u0434\u0430\u0436\u0435 \u0444\u0435\u0440\u043c\u044b, \u0432\u044b\u0440\u0430\u0449\u0438\u0432\u0430\u044e\u0449\u0438\u0435 \u0438\u043d\u0434\u0435\u0435\u043a. \u0410 \u0435\u0441\u043b\u0438 \u0447\u0442\u043e-\u0442\u043e \u0441\u0443\u0449\u0435\u0441\u0442\u0432\u0443\u0435\u0442, \u0437\u043d\u0430\u0447\u0438\u0442 \u0432 \u0438\u043d\u0442\u0435\u0440\u043d\u0435\u0442\u0435 \u043f\u0440\u043e \u044d\u0442\u043e \u0443\u0436\u0435 \u0435\u0441\u0442\u044c\u2026 \u043e\u0442\u043a\u0440\u044b\u0442\u044b\u0439 \u043f\u0440\u043e\u0435\u043a\u0442! \u0421\u043c\u043e\u0442\u0440\u0438\u0442\u0435 \u043a\u0430\u043a Open Data Hub \u043f\u043e\u043c\u043e\u0433\u0430\u0435\u0442 \u043c\u0430\u0441\u0448\u0442\u0430\u0431\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u043d\u043e\u0432\u044b\u0435 \u0442\u0435\u0445\u043d\u043e\u043b\u043e\u0433\u0438\u0438 \u0438 \u0438\u0437\u0431\u0435\u0433\u0430\u0442\u044c \u0442\u0440\u0443\u0434\u043d\u043e\u0441\u0442\u0435\u0439 \u043f\u0440\u0438 \u0438\u0445 \u0432\u043d\u0435\u0434\u0440\u0435\u043d\u0438\u0438. \u041f\u0440\u0438 \u0432\u0441\u0435\u0445 \u043f\u043b\u044e\u0441\u0430\u0445 \u0438\u0441\u043a\u0443\u0441\u0441\u0442\u0432\u0435\u043d\u043d\u043e\u0433\u043e \u0438\u043d\u0442\u0435\u043b\u043b\u0435\u043a\u0442\u0430 (artificial [&hellip;]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":39277,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[688],"tags":[],"class_list":["post-39276","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-administrirovanie"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.2 - aioseo.com -->\n\t<meta name=\"description\" content=\"\u0411\u0443\u0434\u0443\u0449\u0435\u0435 \u043d\u0430\u0441\u0442\u0443\u043f\u0438\u043b\u043e, \u0442\u0435\u0445\u043d\u043e\u043b\u043e\u0433\u0438\u0438 \u0438\u0441\u043a\u0443\u0441\u0441\u0442\u0432\u0435\u043d\u043d\u043e\u0433\u043e \u0438\u043d\u0442\u0435\u043b\u043b\u0435\u043a\u0442\u0430 \u0438 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f \u0443\u0436\u0435 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