{"id":11755,"date":"2024-08-23T08:00:25","date_gmt":"2024-08-23T05:00:25","guid":{"rendered":"https:\/\/diagnozabam.ro\/sfaturi\/?p=11755"},"modified":"2025-04-02T12:37:53","modified_gmt":"2025-04-02T09:37:53","slug":"cum-functioneaza-invatarea-profunda","status":"publish","type":"post","link":"https:\/\/diagnozabam.ro\/sfaturi\/ro\/blog\/cum-functioneaza-invatarea-profunda\/","title":{"rendered":"Cum func\u021bioneaz\u0103 \u00eenv\u0103\u021barea profund\u0103?"},"content":{"rendered":"

Cum func\u021bioneaz\u0103 \u00eenv\u0103\u021barea profund\u0103?<\/h1>\n

\"Cum<\/p>\n

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\u00cenv\u0103\u021barea profund\u0103 (\u00een englez\u0103, deep learning<\/em>) este o ramur\u0103 a \u00eenv\u0103\u021b\u0103rii automate (machine learning) care implic\u0103 utilizarea re\u021belelor neuronale artificiale cu multe straturi pentru a analiza \u0219i a \u00eenv\u0103\u021ba din cantit\u0103\u021bi mari de date complexe. Este inspirat\u0103 de modul \u00een care creierul uman proceseaz\u0103 informa\u021bii, printr-un sistem de neuroni conecta\u021bi care formeaz\u0103 o re\u021bea.<\/p>\n

Cum func\u021bioneaz\u0103 \u00eenv\u0103\u021barea profund\u0103?<\/h3>\n
    \n
  1. Re\u021bele neuronale<\/strong>: Re\u021belele neuronale artificiale sunt structuri matematice compuse din „neuroni” organiza\u021bi \u00een straturi. Un neuron artificial prime\u0219te intr\u0103ri, aplic\u0103 o func\u021bie de activare \u0219i transmite un rezultat mai departe c\u0103tre al\u021bi neuroni din straturile urm\u0103toare.<\/li>\n
  2. Straturi multiple<\/strong>: \u00cenv\u0103\u021barea profund\u0103 utilizeaz\u0103 re\u021bele neuronale cu multe straturi (de aici \u0219i termenul de „profund\u0103”). Acestea pot include zeci sau chiar sute de straturi, fiecare extr\u0103g\u00e2nd caracteristici din ce \u00een ce mai complexe din datele de intrare.<\/li>\n
  3. Antrenare prin date<\/strong>: Re\u021belele neuronale sunt antrenate prin procesul de ajustare a ponderilor conexiunilor dintre neuroni, astfel \u00eenc\u00e2t s\u0103 minimizeze eroarea dintre rezultatele prev\u0103zute \u0219i cele reale. Acest proces implic\u0103 utilizarea unor tehnici cum ar fi backpropagation<\/em> \u0219i algoritmi de optimizare precum gradient descent<\/em>.<\/li>\n
  4. Aplica\u021bii diverse<\/strong>: \u00cenv\u0103\u021barea profund\u0103 este utilizat\u0103 \u00een recunoa\u0219terea imaginilor, procesarea limbajului natural, traducerea automat\u0103, diagnosticare medical\u0103, vehicule autonome \u0219i multe alte domenii.<\/li>\n<\/ol>\n

    Exemple de aplica\u021bii<\/h3>\n
      \n
    • Recunoa\u0219terea imaginii<\/strong>: Re\u021belele neuronale convolu\u021bionale (CNN) sunt un tip de re\u021bea neuronal\u0103 profund\u0103 utilizat\u0103 pentru a recunoa\u0219te obiecte \u0219i caracteristici \u00een imagini.<\/li>\n
    • Procesarea limbajului natural (NLP)<\/strong>: Re\u021bele neuronale recurente (RNN) \u0219i modelele Transformer sunt utilizate pentru traducerea automat\u0103, generarea de text, analiza sentimentului \u0219i chatbot-uri.<\/li>\n
    • Vehicule autonome<\/strong>: \u00cenv\u0103\u021barea profund\u0103 este esen\u021bial\u0103 pentru ca ma\u0219inile autonome s\u0103 \u00een\u021beleag\u0103 mediul din jurul lor, s\u0103 recunoasc\u0103 pietonii, s\u0103 identifice semnele de circula\u021bie \u0219i s\u0103 ia decizii \u00een timp real.<\/li>\n<\/ul>\n

      De ce este important\u0103 \u00eenv\u0103\u021barea profund\u0103?<\/h3>\n

      \u00cenv\u0103\u021barea profund\u0103 a revolu\u021bionat domeniul inteligen\u021bei artificiale, deoarece poate procesa cantit\u0103\u021bi masive de date \u0219i poate \u00eenv\u0103\u021ba s\u0103 identifice modele complexe pe care metodele tradi\u021bionale nu le pot descoperi. Aceasta a permis progrese semnificative \u00een recunoa\u0219terea vocii, traducerea limbajului, generarea de imagini \u0219i multe altele, av\u00e2nd un impact major asupra tehnologiei moderne.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

      Cum func\u021bioneaz\u0103 \u00eenv\u0103\u021barea profund\u0103? \u00cenv\u0103\u021barea profund\u0103 (\u00een englez\u0103, deep learning) este o ramur\u0103 a \u00eenv\u0103\u021b\u0103rii automate (machine learning) care implic\u0103 utilizarea re\u021belelor neuronale artificiale cu multe straturi pentru a analiza…<\/p>\n","protected":false},"author":1,"featured_media":11756,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_sitemap_exclude":false,"_sitemap_priority":"","_sitemap_frequency":"","footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[357],"tags":[1869,8474,2421,10869,8473,10872,10871,10870,9517,5311],"class_list":["post-11755","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-stiri","tag-ai","tag-deep-learning","tag-inteligenta-artificiala","tag-invatare-profunda","tag-machine-learning","tag-nlp","tag-procesare-imagini","tag-retele-neuronale","tag-tehnologie-ai","tag-vehicule-autonome"],"yoast_head":"\nCum func\u021bioneaz\u0103 \u00eenv\u0103\u021barea 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