{"id":41221,"date":"2020-02-06T20:42:46","date_gmt":"2020-02-06T17:42:46","guid":{"rendered":"https:\/\/prohoster.info\/blog\/blog_prohoster\/python-gateway-v-intersystems-iris"},"modified":"2020-02-06T20:42:46","modified_gmt":"2020-02-06T17:42:46","slug":"python-gateway-v-intersystems-iris","status":"publish","type":"post","link":"https:\/\/prohoster.info\/sq\/blog\/python-gateway-v-intersystems-iris","title":{"rendered":"Python Gateway n\u00eb InterSystems IRIS","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Ky artikull \u00ebsht\u00eb mbi Python Gateway \u2014 nj\u00eb projekt komuniteti me kod t\u00eb hapur p\u00ebr platform\u00ebn e t\u00eb dh\u00ebnave InterSystems IRIS. Ky projekt lejon orkestrimin e \u00e7do algoritmi t\u00eb m\u00ebsimit n\u00eb makin\u00eb t\u00eb nd\u00ebrtuar n\u00eb gjuh\u00ebn Python (mjedisi kryesor p\u00ebr shum\u00eb Shkenc\u00ebtar\u00eb t\u00eb T\u00eb Dh\u00ebnave), duke p\u00ebrdorur biblioteka t\u00eb shumta t\u00eb gatshme p\u00ebr t\u00eb krijuar shpejt analiza adaptyve AI\/ML n\u00eb platform\u00ebn InterSystems IRIS. N\u00eb k\u00ebt\u00eb artikull, un\u00eb do t\u00eb tregoj se si InterSystems IRIS mund t\u00eb orkestroj\u00eb proceset n\u00eb gjuh\u00ebn Python, duke realizuar n\u00eb m\u00ebnyr\u00eb efikase transferimin bidirezional t\u00eb t\u00eb dh\u00ebnave dhe krijimin e proceseve inteligjente t\u00eb biznesit.<\/p>\n

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Plani<\/h1>\n

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    \n
  1. Hyrje.<\/li>\n
  2. Veg\u00ebl.<\/li>\n
  3. Instalimi.<\/li>\n
  4. API.<\/li>\n
  5. Interoperabiliteti.<\/li>\n
  6. Jupyter Notebook.<\/li>\n
  7. P\u00ebrfundime.<\/li>\n
  8. Referencat.<\/li>\n
  9. MLToolkit.<\/li>\n<\/ol>\n

    <\/p>\n

    Hyrje<\/h1>\n

    <\/p>\n

    Python \u00ebsht\u00eb nj\u00eb gjuh\u00eb programimi e nivelit t\u00eb lart\u00eb me q\u00ebllim t\u00eb p\u00ebrgjithsh\u00ebm, e orientuar drejt rritjes s\u00eb produktivitetit t\u00eb zhvilluesit dhe lexueshm\u00ebris\u00eb s\u00eb kodit. N\u00eb k\u00ebt\u00eb seri artikujsh, un\u00eb do t\u00eb flas p\u00ebr mund\u00ebsit\u00eb e p\u00ebrdorimit t\u00eb gjuh\u00ebs Python n\u00eb platform\u00ebn InterSystems IRIS, nd\u00ebrsa fokusi kryesor i k\u00ebtij artikulli \u00ebsht\u00eb p\u00ebrdorimi i Python si gjuh\u00eb p\u00ebr krijimin dhe aplikimin e modeleve t\u00eb m\u00ebsimit t\u00eb makin\u00eb.<\/p>\n

    <\/p>\n

    M\u00ebsimi me makin\u00eb (ML) \u00ebsht\u00eb nj\u00eb klas\u00eb metodash t\u00eb inteligjenc\u00ebs artificiale, ku karakteristika dalluese \u00ebsht\u00eb se zgjidhja e problemit nuk b\u00ebhet drejtp\u00ebrdrejt, por p\u00ebrmir\u00ebsohet gjat\u00eb zgjidhjes s\u00eb shum\u00eb problemeve t\u00eb ngjashme. <\/p>\n

    <\/p>\n

    Algoritmet dhe modelet e m\u00ebsimit me makin\u00eb po b\u00ebhen gjithnj\u00eb e m\u00eb t\u00eb zakonshme. Ka shum\u00eb arsye p\u00ebr k\u00ebt\u00eb, por gjith\u00e7ka zvog\u00eblohet n\u00eb aksesibilitetin, thjesht\u00ebsin\u00eb dhe arritjen e rezultateve praktike. A \u00ebsht\u00eb klasterizimi apo madje modelimi me rrjeta nervore nj\u00eb teknologji e re? <\/p>\n

    <\/p>\n

    Sigurisht q\u00eb jo, por aktualisht nuk ka nevoj\u00eb t\u00eb shkruani qindra mij\u00ebra rreshta kodi p\u00ebr t\u00eb vog\u00ebluar nj\u00eb model, nd\u00ebrsa shpenzimet p\u00ebr krijimin dhe zbatimin e modeleve po zvog\u00eblohen vazhdimisht.<\/p>\n

    <\/p>\n

    Mjetet po zhvillohen \u2014 nd\u00ebrsa nuk kemi mjete t\u00eb plot\u00eb t\u00eb orientuara nga GUI p\u00ebr AI\/ML, p\u00ebrparimi q\u00eb kemi v\u00ebzhguar n\u00eb shum\u00eb klasifikime t\u00eb tjera t\u00eb sistemeve informatik\u00eb, p.sh. BI (nga kodimi n\u00eb p\u00ebrdorimin e kornizave dhe zgjidhjeve t\u00eb konfigurueshme t\u00eb orientuara nga GUI), po ndodh gjithashtu n\u00eb mjetet p\u00ebr krijimin e AI\/ML. Ne tashm\u00eb kemi kaluar faz\u00ebn e kodimit dhe sot p\u00ebrdorim korniza p\u00ebr t\u00eb nd\u00ebrtuar dhe trajnuar modelet.<\/p>\n

    <\/p>\n

    P\u00ebrmir\u00ebsime t\u00eb tjera, t\u00eb tilla si mund\u00ebsia p\u00ebr t\u00eb shp\u00ebrndar\u00eb modelin e trajnuar paraprakisht, ku p\u00ebrdoruesi i fundit duhet t\u00eb p\u00ebrfundoj\u00eb thjesht trajnimin e modelit n\u00eb t\u00eb dh\u00ebnat e tij specifike, gjithashtu e thjeshton fillimin e p\u00ebrdorimit t\u00eb m\u00ebsimit t\u00eb makineris\u00eb. K\u00ebto arritje ndihmojn\u00eb ndjesh\u00ebm n\u00eb studimin e m\u00ebsimit t\u00eb makineris\u00eb si p\u00ebr specialist\u00ebt, ashtu edhe p\u00ebr kompanit\u00eb n\u00eb p\u00ebrgjith\u00ebsi.<\/p>\n

    <\/p>\n

    Nga ana tjet\u00ebr, ne po mbledhim gjithnj\u00eb e m\u00eb shum\u00eb t\u00eb dh\u00ebna. Fal\u00eb nj\u00eb platforme t\u00eb unifikuar t\u00eb t\u00eb dh\u00ebnave, si InterSystems IRIS, gjith\u00eb kjo informacion mund t\u00eb p\u00ebrgatitet menj\u00ebher\u00eb dhe t\u00eb p\u00ebrdoret si t\u00eb dh\u00ebna burimore p\u00ebr modelet e m\u00ebsimit t\u00eb makineris\u00eb.<\/p>\n

    <\/p>\n

    Me kalimin n\u00eb cloud, nisja e projekteve AI\/ML b\u00ebhet m\u00eb e leht\u00eb se kurr\u00eb. Ne mund t\u00eb konsumojm\u00eb vet\u00ebm ato resurse q\u00eb na nevojiten. P\u00ebr m\u00eb tep\u00ebr, fal\u00eb paralelizimit q\u00eb ofrojn\u00eb platformat cloud, mund t\u00eb kursejm\u00eb koh\u00ebn e shpenzuar.<\/p>\n

    <\/p>\n

    Por \u00e7far\u00eb b\u00ebhet fjal\u00eb p\u00ebr rezultatet? K\u00ebtu gj\u00ebrat komplikohen. Ekzistojn\u00eb shum\u00eb mjete p\u00ebr nd\u00ebrtimin e modeleve, p\u00ebr t\u00eb cilat do t\u00eb flas m\u00eb tej. T\u00eb nd\u00ebrtosh nj\u00eb model t\u00eb mir\u00eb nuk \u00ebsht\u00eb e leht\u00eb, por \u00e7far\u00eb vjen m\u00eb pas? T\u00eb nxjerr\u00ebsh p\u00ebrfitime nga p\u00ebrdorimi i modelit nga biznesi \u00ebsht\u00eb gjithashtu nj\u00eb detyr\u00eb e komplikuar. Rr\u00ebnja e problemit q\u00ebndron n\u00eb ndarjen e ngarkesave analitike dhe transaksionet, dhe modelet e dh\u00ebnash. Kur e trajnojm\u00eb modelin, zakonisht e b\u00ebjm\u00eb k\u00ebt\u00eb me t\u00eb dh\u00ebna historike. Por vendi p\u00ebr modelin e nd\u00ebrtuar \u00ebsht\u00eb n\u00eb p\u00ebrpunimin transaksional t\u00eb t\u00eb dh\u00ebnave. \u00c7far\u00eb do t\u00eb thot\u00eb t\u00eb kesh modelin m\u00eb t\u00eb mir\u00eb p\u00ebr zbulimin e transaksioneve t\u00eb mashtrimit, n\u00ebse e ekzekutojm\u00eb at\u00eb nj\u00eb her\u00eb n\u00eb dit\u00eb? Mashtruesit tashm\u00eb jan\u00eb larguar me parat\u00eb. Na nevojitet t\u00eb trajnojm\u00eb modelin me t\u00eb dh\u00ebna historike, por gjithashtu duhet ta aplikojm\u00eb at\u00eb n\u00eb koh\u00eb reale me t\u00eb dh\u00ebnat q\u00eb vijn\u00eb, n\u00eb m\u00ebnyr\u00eb q\u00eb proceset tona t\u00eb mund t\u00eb veprojn\u00eb sipas parashikimeve t\u00eb b\u00ebra nga modeli.<\/p>\n

    <\/p>\n

    ML Toolkit \u2014 nj\u00eb grup mjetesh, q\u00ebllimi i t\u00eb cilit \u00ebsht\u00eb pik\u00ebrisht ky: t\u00eb bashkoj\u00eb modelet dhe mjedisin transaksional, n\u00eb m\u00ebnyr\u00eb q\u00eb modelet e nd\u00ebrtuara t\u00eb mund t\u00eb p\u00ebrdoren leht\u00ebsisht n\u00eb proceset tuaja biznesore. Python Gateway \u00ebsht\u00eb nj\u00eb pjes\u00eb e ML Toolkit dhe ofron integrim me gjuh\u00ebn Python (ngjash\u00ebm si R Gateway, q\u00eb gjithashtu \u00ebsht\u00eb pjes\u00eb e ML Toolkit dhe ofron integrim me gjuh\u00ebn R).<\/p>\n

    <\/p>\n

    Instrumentari<\/h1>\n

    <\/p>\n

    Para se t\u00eb vazhdojm\u00eb, do t\u00eb doja t\u00eb p\u00ebrshkruaja disa mjete dhe biblioteka p\u00ebr Python q\u00eb do t\u00eb p\u00ebrdorim m\u00eb von\u00eb.<\/p>\n

    <\/p>\n

    Teknologji<\/h2>\n

    <\/p>\n