{"id":3913,"date":"2023-03-02T19:38:39","date_gmt":"2023-03-02T19:38:39","guid":{"rendered":"https:\/\/www.tsaai.eu\/uporabna-metodologija-umetne-inteligence\/"},"modified":"2023-07-11T22:56:55","modified_gmt":"2023-07-11T22:56:55","slug":"uporabna-metodologija-umetne-inteligence","status":"publish","type":"page","link":"https:\/\/www.tsaai.eu\/sl\/uporabna-metodologija-umetne-inteligence\/","title":{"rendered":"Uporabna metodologija umetne inteligence"},"content":{"rendered":"

Uporabna metodologija umetne inteligence<\/h2><\/div>

<\/i><\/i><\/span>Izvajanje analize podatkov za umetno inteligenco<\/span><\/a><\/h4><\/div>
\n
    \n
  1. Razumevanje delovanja analize<\/li>\n
  2. U\u010dinkovita uporaba analize podatkov s strojnim u\u010denjem<\/li>\n
  3. Dolo\u010danje, kaj lahko umetna inteligenca dose\u017ee<\/li>\n<\/ol>\n<\/div><\/div><\/div>

    <\/i><\/i><\/span>Podatkovna znanost v poslovanju <\/span><\/a><\/h4><\/div>
    \n
      \n
    1. Postopek podatkovne znanosti<\/li>\n
    2. Strojno u\u010denje v poslovanju<\/li>\n
    3. Zajem podatkov<\/li>\n
    4. Priprava podatkov<\/li>\n
    5. Vizualizacija podatkov<\/li>\n
    6. Sklepanje<\/li>\n
    7. Podatkovni in\u017eeniring<\/li>\n
    8. Pristop na podlagi pravil proti pristopu podatkovne znanosti<\/li>\n<\/ol>\n<\/div><\/div><\/div>

      <\/i><\/i><\/span>Oblikovanje sistemov umetne inteligence v proizvodnji <\/span><\/a><\/h4><\/div>
      \n
        \n
      1. Uvod v oblikovanje sistemov umetne inteligence\n
          \n
        1. Poslovni cilji in cilji strojnega u\u010denja<\/li>\n
        2. Zahteve za sisteme umetne inteligence<\/li>\n
        3. Iterativni postopek<\/li>\n
        4. Oblikovanje problemov umetne inteligence<\/li>\n
        5. Um v primerjavi s podatki<\/li>\n<\/ol>\n<\/li>\n
        6. Osnove podatkovnega in\u017eeniringa\n
            \n
          1. Viri podatkov<\/li>\n
          2. Podatkovni formati<\/li>\n
          3. Modeli podatkov<\/li>\n
          4. Motorji za shranjevanje in obdelavo podatkov<\/li>\n
          5. Na\u010dini pretoka podatkov<\/li>\n
          6. Serijska obdelava v primerjavi s preto\u010dno obdelavo<\/li>\n<\/ol>\n<\/li>\n
          7. Podatki za usposabljanje\n
              \n
            1. Vzor\u010denje<\/li>\n
            2. Ozna\u010devanje<\/li>\n
            3. Neuravnote\u017eenost razredov<\/li>\n
            4. Raz\u0161irjenje podatkov<\/li>\n<\/ol>\n<\/li>\n
            5. Oblikovanje zna\u010dilnosti\n
                \n
              1. Nau\u010dene zna\u010dilnosti v primerjavi z na\u010drtovanimi zna\u010dilnostmi<\/li>\n
              2. Obi\u010dajne zna\u010dilnosti In\u017eenirske operacije<\/li>\n
              3. Uhajanje podatkov<\/li>\n
              4. Na\u010drtovanje dobrih lastnosti<\/li>\n<\/ol>\n<\/li>\n
              5. Razvoj modela in vrednotenje brez povezave\n
                  \n
                1. Razvoj modela in usposabljanje<\/li>\n
                2. Vrednotenje modela brez povezave<\/li>\n<\/ol>\n<\/li>\n
                3. Uporaba modela in storitev napovedovanja\n
                    \n
                  1. Miti o uvajanju strojnega u\u010denja<\/li>\n
                  2. Serijsko napovedovanje v primerjavi s spletnim napovedovanjem<\/li>\n
                  3. Stiskanje modela<\/li>\n
                  4. Strojno u\u010denje v oblaku in na robu<\/li>\n<\/ol>\n<\/li>\n
                  5. Premiki in spremljanje distribucije podatkov\n
                      \n
                    1. Vzroki za napake sistemov umetne inteligence<\/li>\n
                    2. Premiki distribucije podatkov<\/li>\n
                    3. Spremljanje in mo\u017enost opazovanja<\/li>\n<\/ol>\n<\/li>\n
                    4. Nenehno u\u010denje in testiranje v produkciji\n
                        \n
                      1. Nenehno u\u010denje<\/li>\n
                      2. Testiranje v proizvodnji<\/li>\n<\/ol>\n<\/li>\n
                      3. Infrastruktura in orodja za MLOps\n
                          \n
                        1. Shranjevanje in ra\u010dunanje<\/li>\n
                        2. Razvojno okolje<\/li>\n
                        3. Upravljanje virov<\/li>\n
                        4. Platforma strojnega u\u010denja<\/li>\n
                        5. Gradnja proti nakupu<\/li>\n<\/ol>\n<\/li>\n
                        6. \u010clove\u0161ka plat umetne inteligence\n
                            \n
                          1. Uporabni\u0161ka izku\u0161nja<\/li>\n
                          2. Struktura ekipe<\/li>\n
                          3. Odgovorna umetna inteligenca<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n<\/div><\/div><\/div>

                            <\/i><\/i><\/span>Metode razlo\u017eljivosti modela <\/span><\/a><\/h4><\/div>
                            \n
                              \n
                            1. Uvod v XAI<\/li>\n
                            2. Opredelitev metod in pristopov za razlago<\/li>\n
                            3. Ocenjevanje kakovosti metod za pojasnjevanje<\/li>\n
                            4. Vrste metod pojasnjevanja modelov<\/li>\n
                            5. Metode pridobivanja znanja<\/li>\n
                            6. Metode, ki temeljijo na vplivu<\/li>\n
                            7. Metode, ki temeljijo na primerih<\/li>\n<\/ol>\n<\/div><\/div><\/div>

                              <\/i><\/i><\/span>Razvoj pravega projekta umetne inteligence <\/span><\/a><\/h4><\/div>
                              \n
                                \n
                              1. Profil in\u017eenirja umetne inteligence<\/li>\n
                              2. Pomembni dejavniki\n
                                  \n
                                1. Razjasnitev razlik med podatkovnim znanstvenikom in in\u017eenirjem umetne inteligence<\/li>\n
                                2. Osredoto\u010danje na preprostost pri vseh projektnih delih za zmanj\u0161anje tveganja<\/li>\n
                                3. Uporaba agilnih temeljev pri projektnem delu na podro\u010dju umetne inteligence<\/li>\n
                                4. Razlike in podobnosti med DevOps in MLOps<\/li>\n<\/ol>\n<\/li>\n
                                5. Na\u010drtovanje in dolo\u010danje obsega projekta<\/li>\n
                                6. Komunikacija in logistika projekta<\/li>\n
                                7. Na\u010drtovanje in raziskovanje projekta umetne inteligence<\/li>\n
                                8. Testiranje in vrednotenje projekta umetne inteligence<\/li>\n
                                9. Prehod od prototipa do MVP<\/li>\n<\/ol>\n<\/div><\/div><\/div><\/div><\/div>
                                  <\/div><\/div><\/div>
                                  <\/span><\/div><\/div><\/div><\/div><\/div>
                                  <\/a><\/div><\/div>

                                  Metode in orodja na podro\u010dju umetne inteligence<\/a><\/h4>\n<\/div><\/div><\/div><\/div><\/div><\/div>
                                  <\/div><\/div>

                                  Uporabna umetna inteligenca v znanosti<\/a><\/h4>\n<\/div><\/div><\/div>
                                  <\/a><\/div><\/div><\/div><\/div><\/div>
                                  <\/div><\/div><\/div><\/div><\/p>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":3,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"100-width.php","meta":{"inline_featured_image":false,"footnotes":""},"class_list":["post-3913","page","type-page","status-publish","hentry"],"yoast_head":"\nUporabna metodologija umetne inteligence - TSAAI<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.tsaai.eu\/sl\/uporabna-metodologija-umetne-inteligence\/\" \/>\n<meta property=\"og:locale\" content=\"sl_SI\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Uporabna metodologija umetne inteligence - TSAAI\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.tsaai.eu\/sl\/uporabna-metodologija-umetne-inteligence\/\" \/>\n<meta property=\"og:site_name\" content=\"TSAAI\" \/>\n<meta property=\"article:modified_time\" content=\"2023-07-11T22:56:55+00:00\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"19 minut\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.tsaai.eu\/sl\/uporabna-metodologija-umetne-inteligence\/\",\"url\":\"https:\/\/www.tsaai.eu\/sl\/uporabna-metodologija-umetne-inteligence\/\",\"name\":\"Uporabna metodologija umetne inteligence - 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