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_الذكاء الاصطناعي .pdf

_الذكاء الاصطناعي

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‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬
Omar Selim
Sunday, 22 August
8 PM (GMT+2)
BIM Manager
&
Omar.selm@gmail.com
https://bimarabia.com/OmarSelim/
‫ﺳﻠﯾم‬ ‫ﻋﻣر‬ ‫اﻧﺎ‬
BIMarabia ‫ﻣؤﺳس‬
BIM ‫ﻣدﯾر‬
‫اﻟﻔﻧﻲ‬ ‫اﻟدﻋم‬ ‫ﻣدﯾر‬ / BIM ‫ﻣدرب‬ / CAD ‫ﻣدﯾر‬ / ‫اﺧﺻﺎﺋﻲ‬
‫ﻣﺻر‬ ‫أﺟل‬ ‫ﻣن‬ ‫ﻣﮭﻧدﺳون‬ ، (‫اﻟﻣﺑﺎﻧﻲ‬ ‫أداء‬ ‫ﻟﻣﺣﺎﻛﺎة‬ ‫اﻟدوﻟﯾﺔ‬ ‫)اﻟراﺑطﺔ‬ IBPSA ‫ﻓﻲ‬ ‫ﻋﺿو‬
‫ﻣﺳﺗداﻣﺔ‬
‫ﻗطر‬ ‫ﺟﺎﻣﻌﺔ‬ ‫ﻓﻲ‬ ‫ﺳﺎﺑق‬ ‫ﺑﺎﺣث‬ ‫ﻣﺳﺎﻋد‬
‫ﻓﻲ‬ ‫ﺧﺑﯾر‬ ‫ﻣﺳﺗﺧدم‬ .‫واﻟﺗﻔﺎﺻﯾل‬ ‫اﻟﻣﻌﻣﺎري‬ ‫واﻟﺗﺧطﯾط‬ ‫اﻟﻣﻌﻣﺎرﯾﺔ‬ ‫اﻟرﺳوﻣﺎت‬ ‫اﻟﺗﺟرﺑﺔ‬ ‫ھذه‬ ‫ﺗﺷﻣل‬
.QTO ‫و‬ AutoCAD ‫و‬ NAVISWORKS ‫و‬ Revit
BIM ‫ﺗﻘﻧﯾﺔ‬ ‫ﺑﺎﺳﺗﺧدام‬ ‫اﻟﻣﺷﺎرﯾﻊ‬ ‫ﻣن‬ ‫اﻟﻌدﯾد‬ ‫ﻓﻲ‬ ‫ﻋﻣﻠت‬ ‫ﻟﻘد‬
‫اﻻﺳﺗﺧداﻣﺎت‬ ‫ﻣﺗﻌددة‬ ‫واﻟﻣﺑﺎﻧﻲ‬ ‫اﻟﻔﻧﺎدق‬ ‫ﻣﺛل‬ ، ‫اﻷﻧواع‬ ‫ﻣن‬ ‫اﻟﻛﺛﯾر‬ ‫اﻟﻣﺷﺎرﯾﻊ‬ ‫ھذه‬ ‫وﺗﺷﻣل‬ ،
‫واﻟﻔﯾﻼت‬ ‫واﻟﻣﺳﺎﺟد‬ ‫واﻟﻣﺳﺗﺷﻔﯾﺎت‬
.‫اﻟﻣﻌرﻓﺔ‬ ‫ﻣﺷﺎرﻛﺔ‬ ‫أﺣب‬ ‫ﻷﻧﻧﻲ‬ ‫ھﻧﺎ‬ ‫أﻧﺎ‬
BIMarabia‫ﻋﻠﻰ‬ ‫ﺗﺟدﻧﻲ‬ ‫أن‬ ‫ﯾﻣﻛﻧك‬
https://bimarabia.com/OmarSelim/
https://bimarabia.com/OmarSelim/
:(Robot ) ‫اﻵﻟﻲ‬ ‫اﻹﻧﺳﺎن‬
‫ھﻲ‬ (Robotics ) ‫اﻵﻟﻲ‬ ‫اﻹﻧﺴﺎن‬ ‫ﺗﻜﻨﻮﻟﻮﺟﯿﺎ‬ ‫إن‬
‫ﻣﻦ‬ ‫ﺗﻘﺪﻣﺎ‬ ‫اﻻﺻﻄﻨﺎﻋﻲ‬ ‫اﻟﺬﻛﺎء‬ ‫ﺗﻜﻨﻮﻟﻮﺟﯿﺎ‬ ‫أﻛﺜﺮ‬ ‫ﻣﻦ‬
‫ﻟﻠﻤﺸﺎﻛﻞ‬ ‫ﻛﺎﻣﻠﺔ‬ ‫ﺣﻠﻮﻻ‬ ‫ﻓﯿﮭﺎ‬ ‫ﺗﻘﺪم‬ ‫اﻟﺘﻲ‬ ‫اﻟﺘﻄﺒﯿﻘﺎت‬ ‫ﺣﯿﺚ‬
‫ﻋﺒﺎرة‬ ‫اﻵﻟﻲ‬ ‫اﻹﻧﺴﺎن‬ ‫أو‬ (Robot ) ‫واﻟﺮﺑﻮرت‬
‫ﺑﻌﺾ‬ ‫ﻟﺘﺆدى‬ ‫ﺑﺮﻣﺠﺘﮭﺎ‬ ‫ﯾﻤﻜﻦ‬ ‫ﻣﯿﻜﺎﻧﯿﻜﯿﺔ‬ ‫آﻟﮫ‬ ‫ﻋﻦ‬
‫ذﻛﺎء‬ ‫ﺑﻨﻔﺲ‬ ‫ﯾﺪوﯾﺎ‬ ‫اﻹﻧﺴﺎن‬ ‫ﺑﮭﺎ‬ ‫ﯾﻘﻮم‬ ‫اﻟﺘﻲ‬ ‫اﻟﻤﮭﺎم‬
. ‫اﻻﻧﺴﺎن‬
https://bimarabia.com/OmarSelim/
https://bimarabia.com/OmarSelim/
‫اﻵﻟﺔ‬
‫اﻟﻘواﻋد‬
‫اﻟﺑﯾﺎﻧﺎت‬
‫اﻹﺟﺎﺑﺎت‬
‫اﻟﺗﻘﻠﯾدﯾﺔ‬ ‫اﻟﺑرﻣﺟﺔ‬
‫اﻵﻟﺔ‬
‫اﻹﺟﺎﺑﺎت‬
‫اﻟﺑﯾﺎﻧﺎت‬
‫اﻟﻘواﻋد‬ Model
‫اﻵﻟﺔ‬ ‫ﺗﻌﻠم‬

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_الذكاء الاصطناعي .pdf

  • 2. https://bimarabia.com/OmarSelim/ ‫ﺳﻠﯾم‬ ‫ﻋﻣر‬ ‫اﻧﺎ‬ BIMarabia ‫ﻣؤﺳس‬ BIM ‫ﻣدﯾر‬ ‫اﻟﻔﻧﻲ‬ ‫اﻟدﻋم‬ ‫ﻣدﯾر‬ / BIM ‫ﻣدرب‬ / CAD ‫ﻣدﯾر‬ / ‫اﺧﺻﺎﺋﻲ‬ ‫ﻣﺻر‬ ‫أﺟل‬ ‫ﻣن‬ ‫ﻣﮭﻧدﺳون‬ ، (‫اﻟﻣﺑﺎﻧﻲ‬ ‫أداء‬ ‫ﻟﻣﺣﺎﻛﺎة‬ ‫اﻟدوﻟﯾﺔ‬ ‫)اﻟراﺑطﺔ‬ IBPSA ‫ﻓﻲ‬ ‫ﻋﺿو‬ ‫ﻣﺳﺗداﻣﺔ‬ ‫ﻗطر‬ ‫ﺟﺎﻣﻌﺔ‬ ‫ﻓﻲ‬ ‫ﺳﺎﺑق‬ ‫ﺑﺎﺣث‬ ‫ﻣﺳﺎﻋد‬ ‫ﻓﻲ‬ ‫ﺧﺑﯾر‬ ‫ﻣﺳﺗﺧدم‬ .‫واﻟﺗﻔﺎﺻﯾل‬ ‫اﻟﻣﻌﻣﺎري‬ ‫واﻟﺗﺧطﯾط‬ ‫اﻟﻣﻌﻣﺎرﯾﺔ‬ ‫اﻟرﺳوﻣﺎت‬ ‫اﻟﺗﺟرﺑﺔ‬ ‫ھذه‬ ‫ﺗﺷﻣل‬ .QTO ‫و‬ AutoCAD ‫و‬ NAVISWORKS ‫و‬ Revit BIM ‫ﺗﻘﻧﯾﺔ‬ ‫ﺑﺎﺳﺗﺧدام‬ ‫اﻟﻣﺷﺎرﯾﻊ‬ ‫ﻣن‬ ‫اﻟﻌدﯾد‬ ‫ﻓﻲ‬ ‫ﻋﻣﻠت‬ ‫ﻟﻘد‬ ‫اﻻﺳﺗﺧداﻣﺎت‬ ‫ﻣﺗﻌددة‬ ‫واﻟﻣﺑﺎﻧﻲ‬ ‫اﻟﻔﻧﺎدق‬ ‫ﻣﺛل‬ ، ‫اﻷﻧواع‬ ‫ﻣن‬ ‫اﻟﻛﺛﯾر‬ ‫اﻟﻣﺷﺎرﯾﻊ‬ ‫ھذه‬ ‫وﺗﺷﻣل‬ ، ‫واﻟﻔﯾﻼت‬ ‫واﻟﻣﺳﺎﺟد‬ ‫واﻟﻣﺳﺗﺷﻔﯾﺎت‬ .‫اﻟﻣﻌرﻓﺔ‬ ‫ﻣﺷﺎرﻛﺔ‬ ‫أﺣب‬ ‫ﻷﻧﻧﻲ‬ ‫ھﻧﺎ‬ ‫أﻧﺎ‬ BIMarabia‫ﻋﻠﻰ‬ ‫ﺗﺟدﻧﻲ‬ ‫أن‬ ‫ﯾﻣﻛﻧك‬
  • 4. https://bimarabia.com/OmarSelim/ :(Robot ) ‫اﻵﻟﻲ‬ ‫اﻹﻧﺳﺎن‬ ‫ھﻲ‬ (Robotics ) ‫اﻵﻟﻲ‬ ‫اﻹﻧﺴﺎن‬ ‫ﺗﻜﻨﻮﻟﻮﺟﯿﺎ‬ ‫إن‬ ‫ﻣﻦ‬ ‫ﺗﻘﺪﻣﺎ‬ ‫اﻻﺻﻄﻨﺎﻋﻲ‬ ‫اﻟﺬﻛﺎء‬ ‫ﺗﻜﻨﻮﻟﻮﺟﯿﺎ‬ ‫أﻛﺜﺮ‬ ‫ﻣﻦ‬ ‫ﻟﻠﻤﺸﺎﻛﻞ‬ ‫ﻛﺎﻣﻠﺔ‬ ‫ﺣﻠﻮﻻ‬ ‫ﻓﯿﮭﺎ‬ ‫ﺗﻘﺪم‬ ‫اﻟﺘﻲ‬ ‫اﻟﺘﻄﺒﯿﻘﺎت‬ ‫ﺣﯿﺚ‬ ‫ﻋﺒﺎرة‬ ‫اﻵﻟﻲ‬ ‫اﻹﻧﺴﺎن‬ ‫أو‬ (Robot ) ‫واﻟﺮﺑﻮرت‬ ‫ﺑﻌﺾ‬ ‫ﻟﺘﺆدى‬ ‫ﺑﺮﻣﺠﺘﮭﺎ‬ ‫ﯾﻤﻜﻦ‬ ‫ﻣﯿﻜﺎﻧﯿﻜﯿﺔ‬ ‫آﻟﮫ‬ ‫ﻋﻦ‬ ‫ذﻛﺎء‬ ‫ﺑﻨﻔﺲ‬ ‫ﯾﺪوﯾﺎ‬ ‫اﻹﻧﺴﺎن‬ ‫ﺑﮭﺎ‬ ‫ﯾﻘﻮم‬ ‫اﻟﺘﻲ‬ ‫اﻟﻤﮭﺎم‬ . ‫اﻻﻧﺴﺎن‬
  • 10. https://bimarabia.com/OmarSelim/ Artificial Intelligence ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫ھو‬ ‫ﻣﺎ‬ step towards” ‫ﻋﻧوان‬ ‫ﺗﺣت‬ 1961 ‫ﻋﺎم‬ ‫ﻣﻘﺎﻟﺔ‬ ‫ﻛﺗب‬ ‫ﻋﻧدﻣﺎ‬ ‫ﻣﻧﻛﺳﻲ‬ ‫ﻣﺎرﻓن‬ ‫اﻟﻌﺎﻟم‬ ‫إﻟﻰ‬ ‫ﯾرﺟﻊ‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫ﻣﺻطﻠﺢ‬ . “Artificial intelligence ‫ﻓﻲ‬ ‫اﻷھداف‬ ‫ﺗﺣﻘﯾق‬ ‫ﻋﻠﻰ‬ ‫اﻟﻘدرة‬ ‫ﯾﻌطﯾﻧﺎ‬ ‫اﻟذي‬ ‫اﻟﺣﺳﺎﺑﻲ‬ ‫اﻟﺟزء‬ ‫اﻋﺗﺑﺎره‬ ‫وﯾﻣﻛن‬ ،‫ﺑدﻗﺔ‬ ‫ﺗﻌرﯾﻔﮫ‬ ‫ﯾﺻﻌب‬ ‫ﻛﻣﻔﮭوم‬ Intelligence ‫اﻟذﻛﺎء‬ .‫اﻟﺗﻌرﯾف‬ ‫ھذا‬ ‫وﻓق‬ ،‫اﻵﻻت‬ ‫وﺑﻌض‬ ‫اﻟﺣﯾواﻧﺎت‬ ‫وﻛذﻟك‬ ،‫اﻟذﻛﺎء‬ ‫ﻣن‬ ‫اﻟدرﺟﺎت‬ ‫ﻣﺧﺗﻠف‬ ‫اﻟﻧﺎس‬ ‫وﻟدى‬ ،‫ﺣوﻟﻧﺎ‬ ‫ﻣن‬ ‫اﻟﻌﺎﻟم‬ : ‫وﺗﻌﻠﻣﮭﺎ‬ ‫اﻷﺷﯾﺎء‬ ‫ﻓﮭم‬ ‫ﻋﻠﻰ‬ ‫اﻟﻘدرة‬ : ‫اﻹﻧﺳﺎن‬ ‫ذﻛﺎء‬ ‫اﻟﻣﺳﺎﺋل‬ ‫ﺣل‬ problems Solving ‫اﻹﺑداع‬ Creativity ‫اﻟﺗﺻﻧﯾف‬ Classification ‫اﻷﻧﻣﺎط‬ ‫اﻛﺗﺷﺎف‬ recognition pattern ‫اﻻﺳﺗﻘراء‬ Induction ‫اﻟﺗﻌﻠم‬ Learning (‫)اﻟﻘﯾﺎس‬ ‫اﻟﻘﯾﺎﺳﺎت‬ ‫ﺑﻧﺎء‬ analogies building ‫اﻻﺳﺗﻧﺗﺎج‬ Deduction ‫اﻟطﺑﯾﻌﯾﺔ‬ ‫اﻟﻠﻐﺔ‬ ‫ﻣﻌﺎﻟﺟﺔ‬ processing language ‫اﻷﻣﺛﻠﺔ‬ ،‫اﻟﺗﺣﺳﯾن‬ Optimization ‫أﺧرى‬ ‫ﻛﺛﯾرة‬ ‫وأﻣﺛﻠﺔ‬ ‫اﻟﻣﻌرﻓﺔ‬ more many and knowledge.
  • 11. https://bimarabia.com/OmarSelim/ ● ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫وﻣﻧذ‬ .‫اﻟﺳﺎﺑﻘﺔ‬ ‫اﻟﺗﺟﺎرب‬ ‫ﻣن‬ ‫واﻻﺳﺗﻔﺎدة‬ ‫واﻻﻛﺗﺷﺎف‬ ،‫اﻟﺗﻔﻛﯾر‬ ‫ﻋﻠﻰ‬ ‫ﻗدرﺗﮫ‬ ‫ﻣﺛل‬ ،‫ﻋﻣﻠﮫ‬ ‫وطرﯾﻘﺔ‬ ‫اﻟﺑﺷري‬ ‫اﻟﻌﻘل‬ ‫ﻣﺣﺎﻛﺎة‬ ‫ﻋﻠﻰ‬ ‫اﻵﻟﺔ‬ ‫ﻗدرة‬ ‫ھو‬ :‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫ﺗﻌرﯾف‬ ‫ّظرﯾﺎت‬‫ﻧ‬‫ﻟﻠ‬ ‫إﺛﺑﺎﺗﺎت‬ ‫اﻛﺗﺷﺎف‬ ‫ﯾﻣﻛﻧﮫ‬ ‫ﺣﯾث‬ ،‫اﻋﺗﻘدﻧﺎ‬ ‫ّﺎ‬‫ﻣ‬‫ﻣ‬ ً‫ا‬‫ﺗﻌﻘﯾد‬ ‫أﻛﺛر‬ ‫ﺑﻣﮭﻣﺎت‬ ‫اﻟﻘﯾﺎم‬ ‫ﺑﺎﺳﺗطﺎﻋﺗﮫ‬ ‫اﻟﺣﺎﺳوب‬ ‫أنﱠ‬ ‫اﻛﺗﺷﺎف‬ ‫ﱠ‬‫م‬‫ﺗ‬ ،‫اﻟﻌﺷرﯾن‬ ‫اﻟﻘرن‬ ‫ﻣﻧﺗﺻف‬ ‫ﻓﻲ‬ ‫اﻟﺣﺎﺳوب‬ ‫ﺷﮭده‬ ‫اﻟذي‬ ‫ر‬ ّ‫اﻟﺗطو‬ ‫ﻻﯾوﺟد‬ ‫ﻟﻶن‬ ‫ّﮫ‬‫ﻧ‬‫أ‬ ‫إﻻ‬ ‫ﻋﺎﻟﯾﺔ‬ ‫ﺗﺧزﯾﻧﯾﺔ‬ ‫وﺳﻌﺔ‬ ‫اﻟﻣﻌﺎﻟﺟﺔ‬ ‫ﻓﻲ‬ ‫ﺳرﻋﺔ‬ ‫ﻣن‬ ‫اﻟﻛﺛﯾرة‬ ‫ّﺎﺗﮫ‬‫ﯾ‬‫إﯾﺟﺎﺑ‬ ‫ﻣن‬ ‫ﺑﺎﻟرﻏم‬ ،‫ذﻟك‬ ‫وﻣﻊ‬ .‫ﻛﺑﯾرة‬ ‫ﺑﻣﮭﺎرة‬ ‫اﻟﺷطرﻧﺞ‬ ‫ﻟﻌب‬ ‫ﻋﻠﻰ‬ ‫ﻟﻘدرﺗﮫ‬ ‫ﺑﺎﻹﺿﺎﻓﺔ‬ ،‫ّدة‬‫ﻘ‬‫اﻟﻣﻌ‬ ‫ّﺔ‬‫ﯾ‬‫اﻟرﯾﺎﺿ‬ .‫ﻟﮫ‬ ‫ّﻌرض‬‫ﺗ‬‫اﻟ‬ ‫ﯾﺗم‬ ‫ﻟﻣﺎ‬ ‫اﻟﺗﻠﻘﺎﺋﯾﺔ‬ ‫اﻟﯾوﻣﯾﺔ‬ ‫اﻻﺳﺗﻧﺗﺎﺟﺎت‬ ‫ﺗﺗطﻠب‬ ‫اﻟﺗﻲ‬ ‫ﺑﺎﻟﻣﮭﻣﺎت‬ ‫ﺑﻘﯾﺎﻣﮫ‬ ‫ﯾﺗﻌﻠق‬ ‫ﺑﻣﺎ‬ ً‫ﺎ‬‫ﺧﺻوﺻ‬ ‫اﻟﺑﺷري‬ ‫اﻟﻌﻘل‬ ‫ﻣروﻧﺔ‬ ‫ﻣﺟﺎراة‬ ‫ﺑﺎﺳﺗطﺎﻋﺗﮫ‬ ‫ﺑرﻧﺎﻣﺞ‬ ‫أي‬ ‫ﻧﺣن‬ ‫ﻣﺛﻠﻧﺎ‬ ‫اﻟﻣﮭﺎم‬ ‫ﻣن‬ ‫اﻟﻌدﯾد‬ ‫وﺗﻧﻔذ‬ ‫اﻟﻛﻣﺑﯾوﺗر‬ ‫ﺧﺻﺎﺋص‬ ‫ﺗﺳﺗﺧدم‬ ‫ﻣﻌﻘدة‬ ‫آﻻت‬ ‫ﺷﺎﻛﻠﺔ‬ ‫ﻋﻠﻰ‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫ﺗﺻﻧﯾﻊ‬ ‫ﺗم‬ ‫ﻛﻣﺎ‬ .‫ﺑﺻﻧﺎﻋﺗﮫ‬ ‫اﻹﻧﺳﺎن‬ ‫ﻗﺎم‬ ‫ذﻛﺎء‬ ‫ھو‬ ،‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫ﺗم‬ ‫ﻟﻘد‬ ،‫ﺑﺎﺧﺗﺻﺎر‬ .‫ﺻﺎﺋﺑﺎ‬ ‫أﻣرا‬ ّ‫د‬‫ﯾﻌ‬ ‫ذﻟك‬ ‫ﻓﺈن‬ ،‫اﻹﻧﺳﺎن‬ ‫ﻣن‬ ‫أﻋﻣق‬ ‫ﺣﺳﯾﺔ‬ ‫ﺑﻘدرة‬ ‫وﺗﺗﻣﺗﻊ‬ ‫اﻟﻔﻌل‬ ‫ﺗرد‬ ‫أﻧﮭﺎ‬ ‫اﻋﺗﺑرﻧﺎ‬ ‫إذا‬ ‫وﻟﻛن‬ ،‫ﻟﻺﻧﺳﺎن‬ ‫ﻣﻣﺎﺛﻠﺔ‬ ‫ﺣواﺳﺎ‬ ‫اﻵﻻت‬ ‫ھذه‬ ‫ﺗﻣﻠك‬ ،‫وﻋﻣوﻣﺎ‬ .‫اﻟﺑﺷر‬ .‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫ﻋﻠﻰ‬ ‫ﻓﺣﺻﻠﻧﺎ‬ ،‫آﻻت‬ ‫داﺧل‬ ‫اﻟﺑﺷري‬ ‫اﻟذﻛﺎء‬ ‫دﻣﺞ‬ ‫ﻧﺳﺗطﯾﻊ‬ ‫ﻻ‬ ‫ﺑﻣﺎ‬ ‫ﻟﻠﻘﯾﺎم‬ ‫ﺗﺳﺧﯾرھﺎ‬ ‫ﺗم‬ ‫ﻟذﻟك‬ ،‫اﻹﻧﺳﺎن‬ ‫وظﺎﺋف‬ ‫ﻣﻊ‬ ‫اﻟﺗﻘﻧﯾﺎت‬ ‫ھذه‬ ‫وظﺎﺋف‬ ‫وﺗﺗﺷﺎﺑﮫ‬ .‫اﻟﺑﺷرﯾﺔ‬ ‫ﻣﺳﺗﻘﺑل‬ ،‫أﻓﺿل‬ ‫ﺣﯾﺎﺗﻧﺎ‬ ‫ﺳﺗﺟﻌل‬ ‫اﻟﺗﻲ‬ ،‫اﻟﺗﻛﻧوﻟوﺟﯾﺎ‬ ‫ھذه‬ ‫ﺗﺷﻛل‬ ،‫آﺧر‬ ‫ﺑﻣﻌﻧﻰ‬ ‫ﻏرار‬ ‫ﻋﻠﻰ‬ ‫ﻣﻌﯾﻧﺎ‬ ‫ﺟﮭﺎزا‬ ‫ّل‬‫ﻐ‬‫ﯾﺷ‬ ‫ﻛﻣﺑﯾوﺗر‬ ‫إﻧﮫ‬ ‫اﻟﻘول‬ ‫وﯾﻣﻛﻧك‬ .‫ﺧﺻﺎﺋﺻﮫ‬ ‫ﯾﻧﺎﺳب‬ ‫اﻟذي‬ ‫اﻟدﻗﯾق‬ ‫اﻟﺗﻌرﯾف‬ ‫أو‬ ‫اﻟﻣﻧﺎﺳب‬ ‫اﻟﻣﻌﺟم‬ ‫ﻧﺟد‬ ‫ﻓﻠن‬ ،‫اﻟﻣﺻطﻠﺢ‬ ‫ھذا‬ ‫ﺗﻌرﯾف‬ ‫ﺣﺎوﻟﻧﺎ‬ ‫وإذا‬ .‫إﻧﺟﺎزه‬ .‫اﻟﺑﺷري‬ ‫اﻟدﻣﺎغ‬ ."‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫ﺗﺳﻣﻰ‬ ‫اﻟﺑﺷري‬ ‫اﻟدﻣﺎغ‬ ‫ﻣﺛل‬ ‫واﻟﺗﻔﻛﯾر‬ ‫اﻟﻌﻣل‬ ‫ﻋﻠﻰ‬ ‫اﻵﻻت‬ ‫ﻗدرة‬ ‫"إن‬ ‫ھﻧﺎك‬ ‫ﻷن‬ ‫ﻧظرا‬ ‫اﻵن‬ ‫ﺣﺗﻰ‬ ‫ﻣﻣﻛن‬ ‫ﻏﯾر‬ ‫أﻣر‬ ‫ﺣﯾﺎﺗﻧﺎ‬ ‫ﻓﻲ‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫إدﻣﺎج‬ ‫ﯾﻌﺗﺑر‬ ،‫ذﻟك‬ ‫وﻣﻊ‬ .‫اﻟﺑﺷري‬ ‫اﻟدﻣﺎغ‬ ‫ﻟﺗﺻﻣﯾم‬ ‫ﻣﺷﺎﺑﮫ‬ ‫ﺑﺷﻛل‬ ‫وﯾﺗﻔﺎﻋل‬ ‫وﯾﻌﻣل‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫ﯾﻔﻛر‬ ‫اﻟذﻛﺎء‬ ‫أﻧظﻣﺔ‬ ‫أﻧواع‬ ‫أھم‬ ‫ﻣن‬ ‫اﻷھﻣﯾﺔ‬ ‫ذات‬ ‫اﻟﺻور‬ ‫ﺗﺻﻧﯾف‬ ‫وﺧدﻣﺔ‬ ‫ﻓﯾﺳﺑوك‬ ‫ﻣوﻗﻊ‬ ‫ﻋﻠﻰ‬ ‫اﻟوﺟوه‬ ‫ﻋﻠﻰ‬ ‫اﻟﺗﻌرف‬ ‫ﻧظﺎم‬ ‫وﯾﻌد‬ .‫وﺻﻔﮭﺎ‬ ‫ﯾﻣﻛن‬ ‫ﻻ‬ ‫اﻟﺗﻲ‬ ‫اﻟﺑﺷري‬ ‫اﻟدﻣﺎغ‬ ‫ﻣﯾزات‬ ‫ﻣن‬ ‫اﻟﻌدﯾد‬ .‫ﯾوﻣﻲ‬ ‫ﺑﺷﻛل‬ ‫ﺗﻌﺗرﺿﻧﺎ‬ ‫اﻟﺗﻲ‬ ،‫اﻷﺧرى‬ ‫اﻷﻣﺛﻠﺔ‬ ‫ﻣن‬ ‫اﻟﻌدﯾد‬ ‫ﻋن‬ ‫ﻓﺿﻼ‬ ،‫اﻻﺻطﻧﺎﻋﻲ‬ .‫ذﻟك‬ ‫إﻟﻰ‬ ‫وﻣﺎ‬ Robo ‫وﻣﺳﺗﺷﺎري‬ ‫اﻟﻘﯾﺎدة‬ ‫ذاﺗﯾﺔ‬ ‫واﻟﺳﯾﺎرات‬ Alexa ‫و‬ Siri ‫ھﻲ‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫ﺑﺎﻟذﻛﺎء‬ ‫اﻟﻣدﻋوﻣﯾن‬ ‫اﻷذﻛﯾﺎء‬ ‫اﻟﻣﺳﺎﻋدﯾن‬ ‫ﻋﻠﻰ‬ ‫اﻷﻣﺛﻠﺔ‬ ‫ﺑﻌض‬ .
  • 12. https://bimarabia.com/OmarSelim/ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫ﻟﺛورة‬ ‫ﻣﺧﺗﺻر‬ ‫ﺗﺎرﯾﺦ‬ ● ‫اﻟﺟزري‬ ‫اﻟرزاز‬ ‫ﺑن‬ ‫إﺳﻣﺎﻋﯾل‬ ‫ﺑن‬ ‫ﺑدﯾﻊ_اﻟزﻣﺎن_أﺑو_اﻟﻌز‬# "‫اﻟﺣﯾل‬ ‫ﺻﻧﺎﻋﺔ‬ ‫ﻓﻲ‬ ‫اﻟﻧﺎﻓﻊ‬ ‫واﻟﻌﻣل‬ ‫اﻟﻌﻠم‬ ‫ﺑﯾن‬ ‫"اﻟﺟﺎﻣﻊ‬ ● . ‫اﻟﻌﻠم‬ ‫ھذا‬ ‫ظﮭور‬ ‫ﺑداﯾﺔ‬ ‫ھﻲ‬ ‫اﻟﺣﺎﺳب‬ ‫ﺑراﻣﺞ‬ ‫ﺗﺧزﯾن‬ ‫ﻋﻠﻰ‬ ‫اﻟﻘدرة‬ ‫ﻟﮭﺎ‬ ‫واﻟﺗﻲ‬ ‫ﺗﯾورﻧﺞ‬ ‫اﻟﺔ‬ ‫ﺗورﻧﻎ‬ ‫آﻻن‬ ‫اﺧﺗراع‬ ● ‫اﻷﻣرﯾﻛﻲ‬ ‫اﻟﻌﺎﻟم‬ ‫ﯾﻌﺗﺑر‬ ‫و‬ . ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫ﺑﺎﻟذﻛﺎء‬ ‫ﺧﺎﺻﺔ‬ ‫ﺑرﻣﺟﺔ‬ ‫ﻟﻐﺔ‬ ‫أول‬ ‫وھﻲ‬ LISP ‫اﻟﻠﯾﺳب‬ ‫ﻟﻐﺔ‬ ‫اﺧﺗراع‬ ‫ﻣن‬ ‫ﻣﺎﻛﺎرﺛﻲ‬ ‫ﺟون‬ ‫ﺗﻣﻛن‬ ‫ﻋﻧدﻣﺎ‬ AI ‫ﻟﻠـ‬ ‫اﻟﺣﻘﯾﻘﺔ‬ ‫اﻟﺑداﯾﺔ‬ the science and engineering of"، ‫ﻋرﻓﮫ‬ ‫وﻗد‬ ،‫م‬١٩٥٦ ‫ﻓﻲ‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫ﻣﺻطﻠﺢ‬ ‫ﺻك‬ ‫اﻟذي‬ ‫ھو‬ McCarthy John ‫ﻣﺎﻛﺎرﺛﻲ‬ ‫ﺟون‬ ‫اﻟذي‬ ‫اﻟﺣﺎﺳوب‬ ‫ﻋﻠوم‬ ‫ﻓرع‬ ‫ھو‬ ‫أو‬ .‫اﻟذﻛﯾﺔ‬ ‫اﻟﺣﺎﺳوب‬ ‫ﺑراﻣﺞ‬ ‫وﺧﺎﺻﺔ‬ ‫اﻟذﻛﯾﺔ‬ ‫اﻵﻻت‬ ‫وھﻧدﺳﺔ‬ ‫ﺻﻧﺎﻋﺔ‬ ‫ﻋﻠم‬ ‫أو‬ "making intelligent machines .‫اﻟذﻛﯾﺔ‬ ‫اﻵﻻت‬ ‫إﻧﺷﺎء‬ ‫إﻟﻰ‬ ‫ﯾﮭدف‬ ● . ‫ﻓﯾزﻧﺑﺎوم‬ ‫ﺟوزﯾف‬ ‫ﺑواﺳطﺔ‬ “ELIZA” ‫ﺳﻣﻲ‬ ‫اﻟﺷطرﻧﺞ‬ ‫ﻟﻌﺑﺔ‬ ‫ﻛﺗﺎﺑﺔ‬ ‫إﻣﻛﺎﻧﯾﺔ‬ 1960 ‫ﻋﺎم‬ ‫ﺷﮭد‬ ● . ‫اﻟطﺑﯾﻌﯾﺔ‬ ‫اﻟﻠﻐﺎت‬ ‫ﻣﻌﺎﻟﺟﺔ‬ , ‫اﻟﺧﺑﯾرة‬ ‫اﻟﻧظم‬ ‫ﻣﺛل‬ ‫ﺑﮫ‬ ‫اﻟﻣﺗﻌﻠﻘﺔ‬ ‫اﻟﻌﻠوم‬ ‫ﺑﻌض‬ ‫ظﮭرت‬ ‫اﻟﺳﺑﻌﯾﻧﯾﺎت‬ ‫ﻧﮭﺎﯾﺔ‬ ‫ﻓﻲ‬ ● ‫ﻓﻲ‬ ‫اﻟﺷطرﻧﺞ‬ ‫ﻓﻲ‬ ‫اﻟﻌﺎﻟم‬ ‫ﺑطل‬ ‫ﻋﻠﻰ‬ ،‫اﻟﻣﺟﺎل‬ ‫ﻓﻲ‬ ‫اﻟراﺋدة‬ IBM ‫ﺷرﻛﺔ‬ ‫ﺻﻧﺎﻋﺔ‬ ‫ﻣن‬ ‫ﺧﺎرق‬ ‫ﺣﺎﺳوب‬ ‫ﻋن‬ ‫ﻋﺑﺎرة‬ ‫وھو‬ ،Deep Blue ‫ﺑﻠو‬ ‫دﯾب‬ ‫ﻓﺎز‬ ،1997 ‫ﻋﺎم‬ ‫اﻹﻧﺳﺎن؟‬ ‫ﻋﻠﻰ‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫ﺳﯾﺗﻔوق‬ ‫أﺧرى‬ ‫ﻣﺟﺎﻻت‬ ‫أي‬ ‫ﻓﻲ‬ ،‫ﺳؤاﻻ‬ ‫وطرﺣت‬ ،‫ﻛﺛﯾرﯾن‬ ‫ﻗﻠوب‬ ‫ﻓﻲ‬ ‫اﻟرﻋب‬ ‫أﺛﺎرت‬ ‫ﻣﺑﺎراة‬ ● .‫ﺑﻧﻔﺳﮭﺎ‬ ‫ﻧﻔﺳﮭﺎ‬ ‫ﺗدﯾر‬ ‫اﻟﺷﻛل‬ ‫داﺋرﯾﺔ‬ ‫ﻣﻛﻧﺳﺔ‬ ‫وھو‬ .‫اﻵﻻف‬ ‫ﻟﻣﺋﺎت‬ ‫اﻟﻣﻧزل‬ ‫رﻓﯾق‬ ‫وأﺻﺑﺢ‬ ،Roomba ‫روﻣﺑﺎ‬ ‫اﻵﻟﻲ‬ ‫اﻹﻧﺳﺎن‬ ‫ظﮭر‬ 2002 ‫وﻓﻲ‬ ● ‫ﻓﻲ‬ ‫ﻋﻠﯾﮫ‬ ‫اﻻﻋﺗﻣﺎد‬ ‫اﻟﺷرﻛﺎت‬ ‫ﺗﺳﺗطﯾﻊ‬ ،‫اﺻطﻧﺎﻋﻲ‬ ‫ذﻛﺎء‬ ‫ﻋﻠﻰ‬ ‫ﯾﺣﺗوي‬ ‫ﺣﺎﺳوب‬ ‫وھو‬ ،‫اﻷﺳواق‬ ‫ﻓﻲ‬ ،Watson ‫واطﺳون‬ ‫اﻟﺣﺎﺳوب‬ ،IBM ‫طرﺣت‬ ،2010 ‫وﻓﻲ‬ .‫واﻟﺗوﻗﻌﺎت‬ ‫اﻟﺻﻌﺑﺔ‬ ‫اﻟﻌﻣﻠﯾﺎت‬ ● ‫وﺣواﺳﯾﺑﮭﺎ‬ ‫ھواﺗﻔﮭﺎ‬ ‫ﻛل‬ ‫ﻓﻲ‬ ‫أﺑل‬ ‫اﻟﺗﻛﻧوﻟوﺟﯾﺎ‬ ‫ﻋﻣﻼق‬ ‫أﻟﺣﻘﺗﮫ‬ ‫اﻟذي‬ ،Siri "‫"ﺳﯾري‬ ‫اﻹﻟﻛﺗروﻧﻲ‬ ‫اﻟﻣﺳﺎﻋد‬ ‫ﺧﻼل‬ ‫ﻣن‬ ‫ﻟﻠﻣﺳﺗﺧدﻣﯾن‬ ‫أﻗرب‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫أﺻﺑﺢ‬ ‫ﺛم‬ .2011 ‫ﻋﺎم‬ ‫ﻓﻲ‬ ● .‫اﻟﻣﺗﺣدة‬ ‫ﺑﺎﻟوﻻﯾﺎت‬ ‫أرﯾزوﻧﺎ‬ ‫وﻻﯾﺔ‬ ‫ﻓﻲ‬ 2020 ‫ﻓﻲ‬ ‫أطﻠﻘﺗﮭﺎ‬ ‫واﻟﺗﻲ‬ ،‫ﺳﺎﺋق‬ ‫ﺑﻼ‬ ‫ﺗﺎﻛﺳﻲ‬ ‫ﺧدﻣﺔ‬ ‫أول‬ ‫ﺗﺟرﺑﺔ‬ ‫ﻓﻲ‬ ‫اﻷﻣرﯾﻛﯾﺔ‬Waymo ‫واﯾﻣو‬ ‫ﺷرﻛﺔ‬ ‫ﺑدأت‬ ،2017 ‫ﻓﻲ‬ ● ‫ﺻوﻓﯾﺎ‬ ‫ﺣﺻﻠت‬ ،‫ﺻوﻓﯾﺎ‬ ‫اﻵﻟﯾﺔ‬ ‫أﺷﮭرھم‬ ‫وﻛﺎن‬ ،Humanoid "‫"ھﯾوﻣﺎﻧوﯾد‬ ‫اﻹﻧﺳﺎن‬ ‫ﻟﺷﻛل‬ ‫اﻟﻣﺣﺎﻛﻲ‬ ‫اﻟطراز‬ ‫ﻣن‬ ‫اﻵﻟﯾﯾن‬ ‫ﻣن‬ ‫ﻟﻧوع‬ ‫ﻛﺑﯾرا‬ ‫ﺗطورا‬ ‫ﻧﻔﺳﮫ‬ ‫اﻟﻌﺎم‬ ‫ﺷﮭد‬ .‫ﻋﺎدي‬ ‫ﺑﺷري‬ ‫ﻛﺄي‬ ‫وﺣﻘوق‬ ‫ﻗﺎﻧوﻧﯾﺔ‬ ‫ﺻﻔﺔ‬ ‫ﻋﻠﻰ‬ ‫آﻟﻲ‬ ‫إﻧﺳﺎن‬ ‫ﻓﯾﮫ‬ ‫ﯾﺣﺻل‬ ‫اﻟذي‬ ‫ﻧوﻋﮫ‬ ‫ﻣن‬ ‫اﻷول‬ ‫اﻟﺣدث‬ ‫ھو‬ ‫ھذا‬ ‫ﻟﯾﻛون‬ ،‫اﻟﺳﻌودﯾﺔ‬ ‫اﻟﺟﻧﺳﯾﺔ‬ ‫ﻋﻠﻰ‬ 2017 ‫ﻓﻲ‬ ● ‫اﻟﺟدال‬ ‫ﻋﻠﻰ‬ ‫اﻟﻘدرة‬ ‫ﻟدﯾﮫ‬ ‫ﺣﺎﺳوب‬ ‫وھو‬ ،"‫اﻟﻣﺟﺎدل‬ ‫ﺑـ"ﻣﺷروع‬ ‫ﺳﻣﻲ‬ ‫ﻣﺎ‬ ،IBM ‫ﺷرﻛﺔ‬ ‫أﺻدرت‬ ‫ﺣﯾث‬ ،‫اﻟﺗﺎﻟﯾﺔ‬ ‫اﻟﺳﻧوات‬ ‫ﻓﻲ‬ ‫اﻟﺗطور‬ ‫ﻓﻲ‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫اﺳﺗﻣر‬ .‫اﻟظﮭور‬ ‫ﻓﻲ‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫ﺻﻧﻊ‬ ‫ﻣن‬ ‫وﻣﻘﺎﻻت‬ ‫ﻓﻧﯾﺔ‬ ‫أﻋﻣﺎل‬ ‫وﺑدأت‬ ،‫اﻟﻣﻧطﻘﯾﺔ‬ ‫اﻟﻘﺿﺎﯾﺎ‬ ‫ﻓﻲ‬ ‫اﻟﺑﺷر‬ ‫ﻣﻊ‬ /https://research.ibm.com/interactive/project-debater
  • 13. https://bimarabia.com/OmarSelim/ ‫؟‬ ‫ذﻛﯾﺔ‬ ‫ﺑﺄﻧﮭﺎ‬ ‫اﻵﻟﺔ‬ ‫ﻋﻠﻰ‬ ‫ﻧطﻠق‬ ‫ﻣﺗﻰ‬ ⚫ Turing test ‫ﺑﺎﺳﺘﺨﺪام‬ ،‫اﻻﻟﺔ‬ ‫ذﻛﺎء‬ ‫ﻣﻦ‬ ‫ﻟﻠﺘﺎﻛﺪ‬ ‫اﺧﺘﺒﺎر‬ ‫ﺗﻮرﻧﺞ‬ ‫اﺑﺘﺪع‬ · ‫و‬ ‫ﻣﻐﻠﻘﺔ‬ ‫ﺣﺠﺮة‬ ‫ﻓﻲ‬ ‫اﻻﻟﺔ‬ ‫وﺿﻊ‬ ‫طﺮﯾﻖ‬ ‫ﻋﻦ‬ ‫ﻣﺘﺼﻼن‬ ‫اﺧﺮى‬ ‫ﻣﻐﻠﻘﺔ‬ ‫ﺣﺠﺮة‬ ‫ﻓﻲ‬ ‫آﺧﺮ‬ ‫إﻧﺴﺎﻧﺎ‬ ‫اﻟﺬي‬ ‫ھﻮ‬ ‫و‬ ، ‫اﻟﺤﻜﻢ‬ ‫ﺑﻐﺮﻓﺔ‬ ‫طﺮﻓﯿﺔ‬ ‫ﺑﻨﮭﺎﯾﺎت‬ ‫و‬ ‫اﻻول‬ ‫اﻻﻧﺴﺎن‬ ‫و‬ ‫ﺑﺎﻻﻟﺔ‬ ‫اﻻﺗﺼﺎل‬ ‫ﯾﺘﻮﻟﻰ‬ ‫و‬ ‫اﻵﻟﺔ‬ ‫ﻣﻦ‬ ‫ﻛﻞ‬ ‫ﻣﻊ‬ ‫ﺣﻮار‬ ‫إدارة‬ ‫اﻟﺤﻜﻢ‬ ‫ﯾﺘﻮﻟﻰ‬ ‫ﻣﻦ‬ ‫ﺗﺤﺪﯾﺪ‬ ‫اﻻﺧﺘﺒﺎر‬ ‫ﻣﻦ‬ ‫واﻟﮭﺪف‬ , ‫اﻹﻧﺴﺎن‬ ‫طﺮح‬ ‫طﺮﯾﻖ‬ ‫ﻋﻦ‬ ‫اﻻﻟﺔ‬ ‫ھﻮ‬ ‫وﻣﻦ‬ ‫اﻟﺮﺟﻞ‬ ‫ھﻮ‬ ‫ﻧﺤﻜﻢ‬ ‫ﺑﯿﻨﮭﻤﺎ‬ ‫اﻟﺘﻔﺮﯾﻖ‬ ‫ﯾﺴﺘﻄﻊ‬ ‫ﻟﻢ‬ ‫ﻓﺎذا‬ ‫اﻻﺳﺌﻠﺔ‬ . ‫ذﻛﯿﺔ‬ ‫ﺑﺄﻧﮭﺎ‬ ‫اﻵﻟﺔ‬ ‫ﻋﻠﻰ‬
  • 15. https://bimarabia.com/OmarSelim/ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫ﺗطﺑﯾﻘﺎت‬ Artificial Intelligence (AI) Facial Recognition Natural Language Processing (NLP) Image and Pattern Recognition Robotics Vision ‫ﺳﻣﻊ‬ ‫واﻟﻛﻼم‬ ‫اﻟﺻوت‬ ‫ﻋﻠﻰ‬ ‫اﻟﺗﻌرف‬ Expert Systems Natural Language Understanding (NLU) Natural Language Generation (NLG) ‫اﻵﻟﺔ‬ ‫ﺗﻌﻠم‬ (ML) ‫اﻟﻌﻣﯾق‬ ‫اﻟﺗﻌﻠم‬ (DL) ‫اﻟﻌﺻﺑﯾﺔ‬ ‫اﻟﺷﺑﻛﺎت‬
  • 16. https://bimarabia.com/OmarSelim/ : symbolic representation ‫اﻟرﻣزي‬ ‫اﻟﺗﻣﺛﯾل‬ (1) ‫ﺗﻤﺜﯿﻞ‬ ‫ﺷﻜﻞ‬ ‫ﻣﻦ‬ ‫ﯾﻘﺘﺮب‬ ‫ﺗﻤﺜﯿﻞ‬ ‫ھﻮ‬ ‫و‬ ‫زﻛﯿﺔ‬ ‫راﺋﺤﺔ‬ ‫ﻟﮫ‬ ‫اﻟﻄﻌﺎم‬ ‫و‬ . ‫ﺟﯿﺪة‬ ‫ﺻﺤﺔ‬ ‫ﻓﻲ‬ ‫اﺣﻤﺪ‬ ‫و‬ . ‫اﻟﻮﻗﻮد‬ ‫ﻣﻦ‬ ‫ﺧﺎﻟﯿﺔ‬ ‫اﻟﺴﯿﺎرة‬ ‫و‬ . ‫ﺣﺎر‬ ‫اﻟﯿﻮم‬ ‫اﻟﺠﻮ‬ : ‫ﻣﺜﻞ‬ ‫اﻟﻤﺘﻮﻓﺮة‬ ‫اﻟﻤﻌﻠﻮﻣﺎت‬ ‫ﻋﻦ‬ ‫ﺗﻌﺒﺮ‬ ‫رﻣﻮز‬ ‫ﻣﻊ‬ ‫ﺗﺘﻌﺎﻣﻞ‬ . ‫اﻟﯿﻮﻣﯿﺔ‬ ‫ﺣﯿﺎﺗﮫ‬ ‫ﻓﻲ‬ ‫ﻟﻤﻌﻠﻮﻣﺎﺗﮫ‬ ‫اﻹﻧﺴﺎن‬ Searching : ‫اﻟﺗﺟرﯾﺑﻲ‬ ‫اﻟﺑﺣث‬ (2) ‫ﺑﺘﺸﺨﯿﺺ‬ ‫ﯾﻘﻮم‬ ‫اﻟﺬي‬ ‫اﻟﻄﺒﯿﺐ‬ ‫ﺣﺎل‬ ‫ھﻮ‬ ‫ﻛﻤﺎ‬ ‫اﻟﺘﺠﺮﯾﺒﻲ‬ ‫اﻟﺒﺤﺚ‬ ‫أﺳﻠﻮب‬ ‫ﻓﯿﮭﺎ‬ ‫ﯾﺘﺒﻊ‬ ‫إذ‬ . ‫ﻣﺤﺪدة‬ ‫ﻣﻨﻄﻘﯿﺔ‬ ‫ﻟﺨﻄﻮات‬ ‫ﺗﺒﻌﺎ‬ ‫اﯾﺠﺎدھﺎ‬ ‫ﯾﻤﻜﻦ‬ ‫ﺣﻠﻮل‬ ‫ﻟﮭﺎ‬ ‫ﺗﺘﻮاﻓﺮ‬ ‫ﻻ‬ ‫ﻣﺸﺎﻛﻞ‬ ‫ﻧﺤﻮ‬ ‫اﻻﺻﻄﻨﺎﻋﻲ‬ ‫اﻟﺬﻛﺎء‬ ‫ﺑﺮاﻣﺞ‬ ‫ﺗﺘﻮﺟﮫ‬ ‫ﻋﻠﻰ‬ ‫اﻟﺤﺎل‬ ‫ﯾﻨﻄﺒﻖ‬ ‫و‬ ، ‫اﻟﺤﻞ‬ ‫إﻟﻰ‬ ‫اﻟﻮﺻﻮل‬ ‫ﻣﻦ‬ ‫آھﺎﺗﮫ‬ ‫ﺳﻤﺎع‬ ‫و‬ ‫ﻟﻠﻤﺮﯾﺾ‬ ‫رؤﯾﺘﮫ‬ ‫ﺑﻤﺠﺮد‬ ‫ﯾﺘﻤﻜﻦ‬ ‫ﻟﻦ‬ ‫و‬ ، ‫اﻟﺪﻗﯿﻖ‬ ‫اﻟﺘﺸﺨﯿﺺ‬ ‫إﻟﻰ‬ ‫اﻟﺘﻮﺻﻞ‬ ‫ﻗﺒﻞ‬ ‫اﻻﺣﺘﻤﺎﻻت‬ ‫ﻣﻦ‬ ‫ﻋﺪد‬ ‫اﻟﻄﺒﯿﺐ‬ ‫ھﺬا‬ ‫ﻓﺄﻣﺎم‬ ، ‫ﻟﻠﻤﺮﯾﺾ‬ ‫اﻟﻤﺮض‬ ‫ﻛﻤﺎ‬ ، ‫اﻟﺤﺎﺳﺐ‬ ‫ﻓﻲ‬ ‫ﻛﺒﯿﺮة‬ ‫ﺗﺨﺰﯾﻦ‬ ‫ﺳﻌﺔ‬ ‫ﺗﻮاﻓﺮ‬ ‫ﺿﺮورة‬ ‫إﻟﻰ‬ ‫ﯾﺤﺘﺎج‬ ‫اﻟﺘﺠﺮﯾﺒﻲ‬ ‫اﻟﺒﺤﺚ‬ ‫ﻣﻦ‬ ‫اﻷﺳﻠﻮب‬ ‫ھﺬا‬ ‫و‬ ، ‫ﻣﺘﻌﺪدة‬ ‫اﻓﺘﺮاﺿﺎت‬ ‫و‬ ‫اﺣﺘﻤﺎﻻت‬ ‫ﺑﺚ‬ ‫ﺑﻌﺪ‬ ‫ﯾﺘﻢ‬ ‫اﻟﺘﺎﻟﯿﺔ‬ ‫اﻟﺨﻄﻮة‬ ‫ﺣﺴﺎب‬ ‫ﻓﺎن‬ ، ‫اﻟﺸﻄﺮﻧﺞ‬ ‫ﻻﻋﺐ‬ . ‫دراﺳﺘﮭﺎ‬ ‫و‬ ‫اﻟﻜﺜﯿﺮة‬ ‫اﻻﺣﺘﻤﺎﻻت‬ ‫ﻟﻔﺮض‬ ‫اﻟﮭﺎﻣﺔ‬ ‫اﻟﻌﻮاﻣﻞ‬ ‫ﻣﻦ‬ ‫اﻟﺤﺎﺳﺐ‬ ‫ﺳﺮﻋﺔ‬ ‫ﺗﻌﺘﺒﺮ‬ : knowledge representation KR ‫ﺗﻣﺛﯾﻠﮭﺎ‬ ‫و‬ ‫اﻟﻣﻌرﻓﺔ‬ ‫اﺣﺗﺿﺎن‬ (3 ) ً‫ﻻ‬‫أو‬ ‫ﻓﮭﻤﮭﺎ‬ ‫ﻣﻦ‬ ‫ّﻨﮫ‬‫ﻜ‬‫ﻧﻤ‬ ‫أن‬ ‫ﯾﺠﺐ‬ ،‫ﻣﺸﺎﻛﻠﻨﺎ‬ ‫ﺣﻞ‬ ‫ﻣﻦ‬ ‫اﻟﺤﺎﺳﺐ‬ ‫ّﻦ‬‫ﻜ‬‫ﻟﻨﻤ‬ ‫اﻟﺬﻛﺎء‬ ‫ﺑﺮاﻣﺞ‬ ‫ﻓﺎن‬ ‫اﻟﺤﻠﻮل‬ ‫إﯾﺠﺎد‬ ‫ﻓﻲ‬ ‫اﻟﺘﺠﺮﯾﺒﻲ‬ ‫اﻟﺒﺤﺚ‬ ‫طﺮق‬ ‫اﺗﺒﺎع‬ ‫و‬ ، ‫اﻟﻤﻌﻠﻮﻣﺎت‬ ‫ﻋﻦ‬ ‫اﻟﺘﻌﺒﯿﺮ‬ ‫ﻓﻲ‬ ‫اﻟﺮﻣﺰي‬ ‫اﻟﺘﻤﺜﯿﻞ‬ ‫أﺳﻠﻮب‬ ‫اﺳﺘﺨﺪام‬ ‫اﻻﺻﻄﻨﺎﻋﻲ‬ ‫اﻟﺬﻛﺎء‬ ‫ﺑﺮاﻣﺞ‬ ‫ﻓﻲ‬ ‫اﻟﮭﺎﻣﺔ‬ ‫اﻟﺨﺼﺎﺋﺺ‬ ‫ﻣﻦ‬ ‫ﻛﺎن‬ ‫ﻟﻤﺎ‬ : ‫ذﻟﻚ‬ ‫ﻣﺜﻞ‬ ‫واﻟﻨﺘﺎﺋﺞ‬ ‫اﻟﺤﺎﻻت‬ ‫ﺑﯿﻦ‬ ‫اﻟﺮﺑﻂ‬ ‫ﻋﻠﻰ‬ ‫ﺗﺤﺘﻮي‬ ‫اﻟﻤﻌﺮﻓﺔ‬ ‫ﻣﻦ‬ ‫ﻛﺒﯿﺮة‬ ‫ﻗﺎﻋﺪة‬ ‫ﺑﻨﺎﺋﮭﺎ‬ ‫ﻓﻲ‬ ‫ﺗﻤﺘﻠﻚ‬ ‫أن‬ ‫ﯾﺠﺐ‬ ‫اﻻﺻﻄﻨﺎﻋﻲ‬ : ‫ذﻟﻚ‬ ‫ﻣﺜﺎل‬ ‫و‬ . ‫اﻟﻤﻌﻄﻒ‬ ‫ارﺗﺪاء‬ ‫ﻓﯿﺠﺐ‬ * . ‫ﻣﻨﺨﻔﻀﺔ‬ ‫اﻟﺤﺮارة‬ ‫درﺟﺔ‬ ‫و‬ * . ‫ﺻﺤﻮ‬ ‫ﻏﯿﺮ‬ ‫اﻟﺠﻮ‬ ‫ﻛﺎن‬ ‫إذا‬ * ‫اﻟﻌﻄﻒ‬ ‫ارﺗﺪاء‬ ‫وﺟﻮب‬ ‫ﺑﻤﻌﺮﻓﺔ‬ ‫اﻟﻤﻌﺮﻓﺔ‬ ‫واﺣﺘﻀﺎن‬ ،( ‫ﺻﺤﻮ‬ ‫ﻏﯿﺮ‬ ‫)اﻟﺠﻮ‬ ‫اﻟﺮﻣﺰي‬ ‫اﻟﺘﻤﺜﯿﻞ‬ ‫ﯾﺘﻀﺢ‬ ‫اﻷﻣﺜﻠﺔ‬ ‫ھﺬه‬ ‫ﻓﻲ‬ ‫و‬ uncertain or uncompleted data : ‫اﻟﻣﻛﺗﻣﻠﺔ‬ ‫ﻏﯾر‬ ‫أو‬ ‫اﻟﻣؤﻛدة‬ ‫ﻏﯾر‬ ‫اﻟﺑﯾﺎﻧﺎت‬ (4 ‫اﻟﺤﻠﻮل‬ ‫ﻛﺎﻧﺖ‬ ‫ﻣﮭﻤﺎ‬ ‫ﺣﻠﻮل‬ ‫ﺑﺈﻋﻄﺎء‬ ‫ﺗﻘﻮم‬ ‫أن‬ ‫ذﻟﻚ‬ ‫ﻣﻌﻨﻰ‬ ‫ﻟﯿﺲ‬ ‫و‬ ، ‫ﻣﻜﺘﻤﻠﺔ‬ ‫أو‬ ‫ﻣﺆﻛﺪة‬ ‫ﻏﯿﺮ‬ ‫اﻟﺒﯿﺎﻧﺎت‬ ‫ﻛﺎﻧﺖ‬ ‫إذا‬ ‫ﺣﻠﻮل‬ ‫إﻋﻄﺎء‬ ‫ﻣﻦ‬ ‫ﺗﺘﻤﻜﻦ‬ ‫أن‬ ‫اﻻﺻﻄﻨﺎﻋﻲ‬ ‫اﻟﺬﻛﺎء‬ ‫ﻣﺠﺎل‬ ‫ﻓﻲ‬ ‫ﺗﺼﻤﻢ‬ ‫اﻟﺘﻲ‬ ‫اﻟﺒﺮاﻣﺞ‬ ‫ﻋﻠﻰ‬ ‫ﯾﺠﺐ‬ ‫اﻟﺤﺼﻮل‬ ‫دون‬ ‫اﻟﺤﺎﻻت‬ ‫ﻣﻦ‬ ‫ﺣﺎﻟﺔ‬ ‫ﻋﺮﺿﺖ‬ ‫ﻣﺎ‬ ‫إذا‬ ‫اﻟﻄﺒﯿﺔ‬ ‫اﻟﺒﺮاﻣﺞ‬ ‫ﻓﻔﻲ‬ ، ‫ﻗﺎﺻﺮة‬ ‫ﺗﺼﺒﺢ‬ ‫إﻻ‬ ‫و‬ ‫اﻟﻤﻘﺒﻮﻟﺔ‬ ‫اﻟﺤﻠﻮل‬ ‫إﻋﻄﺎء‬ ‫ﻋﻠﻰ‬ ‫ﻗﺎدرة‬ ‫ﺗﻜﻮن‬ ‫أن‬ ‫اﻟﺠﯿﺪ‬ ‫ﺑﺄداﺋﮭﺎ‬ ‫ﺗﻘﻮم‬ ‫ﻟﻜﻲ‬ ‫ﯾﺠﺐ‬ ‫إﻧﻤﺎ‬ ‫و‬ ، ‫ﺻﺤﯿﺤﺔ‬ ‫أم‬ ‫ﺧﺎطﺌﺔ‬ . ‫اﻟﺤﻠﻮل‬ ‫إﻋﻄﺎء‬ ‫ﻋﻠﻰ‬ ‫اﻟﻘﺪرة‬ ‫ﻋﻠﻰ‬ ‫اﻟﺒﺮﻧﺎﻣﺞ‬ ‫ﯾﺤﺘﻮي‬ ‫أن‬ ‫ﻓﯿﺠﺐ‬ ‫اﻟﻄﺒﯿﺔ‬ ‫اﻟﺘﺤﻠﯿﻼت‬ ‫ﻧﺘﺎﺋﺞ‬ ‫ﻋﻠﻰ‬ ability to learn : ‫اﻟﺗﻌﻠم‬ ‫ﻋﻠﻰ‬ ‫اﻟﻘدرة‬ (5) ‫ﺗﻌﺘﻤﺪ‬ ‫أن‬ ‫ﯾﺠﺐ‬ ‫اﻻﺻﻄﻨﺎﻋﻲ‬ ‫اﻟﺬﻛﺎء‬ ‫ﺑﺮاﻣﺞ‬ ‫ﻓﺎن‬ ‫اﻟﻤﺎﺿﻲ‬ ‫أﺧﻄﺎء‬ ‫ﻣﻦ‬ ‫اﻻﺳﺘﻔﺎدة‬ ‫أو‬ ‫اﻟﻤﻼﺣﻈﺔ‬ ‫طﺮﯾﻖ‬ ‫ﻋﻦ‬ ‫ﯾﺘﻢ‬ ‫اﻟﺒﺸﺮ‬ ‫ﻓﻲ‬ ‫اﻟﺘﻌﻠﻢ‬ ‫أﻛﺎن‬ ‫ﺳﻮاء‬ ‫و‬ ‫اﻟﺬﻛﻲ‬ ‫اﻟﺴﻠﻮك‬ ‫ﻣﻤﯿﺰات‬ ‫إﺣﺪى‬ ‫اﻟﺘﻌﻠﻢ‬ ‫ﻋﻠﻰ‬ ‫اﻟﻘﺪرة‬ ‫ﺗﻌﺘﺒﺮ‬ . ‫اﻵﻟﺔ‬ ‫ﻟﺘﻌﻠﻢ‬ ‫اﺳﺘﺮاﺗﯿﺠﯿﺎت‬ ‫ﻋﻠﻰ‬ :‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫ﺑراﻣﺞ‬ ‫ﺧﺻﺎﺋص‬
  • 17. https://bimarabia.com/OmarSelim/ Wéiqí ‫ﻟﻛل‬ ‫ﺣرﻛﺔ‬ 20 ‫ھﻧﺎك‬ ‫اﻟﺷطرﻧﺞ‬ ‫ﻓﻔﻲ‬ ،‫اﻟﺷطرﻧﺞ‬ ‫ﻣن‬ ‫أﺻﻌب‬ ‫ھﻲ‬ ‫ﺑل‬ ،‫اﻟﻌﺎﻟم‬ ‫ﻓﻲ‬ ‫ﻟﻌﺑﺔ‬ ‫أﺻﻌب‬ ‫ﺗﻌد‬ Wéiqí ‫ﺗﺷﻲ‬ ‫وي‬ ‫ﺑﺎﻟﺻﯾﻧﯾﺔ‬ ‫أو‬ ‫ﻏو‬ ‫ﻟﻌﺑﺔ‬ ‫ﻓﻲ‬ 1997 ‫ﺳﻧﺔ‬ ‫ﻛﺎﺳﺑﺎروف‬ ‫ﻏﺎري‬ ‫ﻋﻠﻰ‬ ‫ﺑﻠو‬ ‫دﯾب‬ ‫اﻟﻛﻣﺑﯾوﺗر‬ ‫ﺗﻐﻠب‬ ‫ﻟﻘد‬ ،‫اﻟﻠﻌﺑﺔ‬ ‫ﻓﻲ‬ ‫ﻣوﻗﻊ‬ ‫ﻟﻛل‬ ‫ﺣرﻛﺔ‬ 200 ‫ھﻧﺎك‬ ‫ﻓﺈن‬ ‫ﻏو‬ ‫ﻓﻲ‬ ‫وﻟﻛن‬ ،‫ﻣوﻗﻊ‬ ‫ﻟﻌﺑﺔ‬ ‫أﺻﻌب‬ ‫آﺧر‬ ‫وھﻲ‬ ،‫ﻏو‬ ‫ﻟﻌﺑﺔ‬ ‫ﻓﻲ‬ ‫اﻹﻧﺳﺎن‬ ‫ﻋﻠﻰ‬ ‫اﻟﻛﻣﺑﯾوﺗر‬ ‫ﺗﻐﻠب‬ 2015 ‫ﺳﻧﺔ‬ ‫وﻓﻲ‬ ،1996 ‫ﺳﻧﺔ‬ (‫)اﻟﻛﻣﺑﯾوﺗر‬ ‫ﺧﺳﺎرﺗﮫ‬ ‫ﺑﻌد‬ ‫اﻟﺷطرﻧﺞ‬ .‫ﻟﻌﺑﮭﺎ‬ ‫ﻋﻠﻰ‬ ‫ﺑﻘدرﺗﮫ‬ ‫اﻹﻧﺳﺎن‬ ‫ﯾﺗﻣﯾز‬
  • 20. https://bimarabia.com/OmarSelim/ Intelligence of machines today ●The main focus in AI today is getting a computer to recognize, make senses and recreate in what it sees and hears. ●Acting according to us. ●Recognizing a face. ●Navigating a busy street. ●Understanding what someone says.
  • 21. https://bimarabia.com/OmarSelim/ 1 ‫ق‬‫ﯾ‬‫ﺿ‬‫ﻟ‬‫ا‬ ‫ﻲ‬‫ﻋ‬‫ﺎ‬‫ﻧ‬‫ط‬‫ﺻ‬‫ﻻ‬‫ا‬ ‫ء‬‫ﺎ‬‫ﻛ‬‫ذ‬‫ﻟ‬‫ا‬ ‫ص‬‫ﺻ‬‫ﺧ‬‫ﺗ‬‫ﯾ‬ ‫ي‬‫ذ‬‫ﻟ‬‫ا‬ ‫ﻲ‬‫ﻋ‬‫ﺎ‬‫ﻧ‬‫ط‬‫ﺻ‬‫ﻻ‬‫ا‬ ‫ء‬‫ﺎ‬‫ﻛ‬‫ذ‬‫ﻟ‬‫ا‬ ‫و‬‫ھ‬‫و‬ ‫د‬‫ﺣ‬‫ا‬‫و‬ ‫ل‬‫ﺎ‬‫ﺟ‬‫ﻣ‬ ‫ﻲ‬‫ﻓ‬ 2 ‫م‬‫ﺎ‬‫ﻌ‬‫ﻟ‬‫ا‬ ‫ﻲ‬‫ﻋ‬‫ﺎ‬‫ﻧ‬‫ط‬‫ﺻ‬‫ﻻ‬‫ا‬ ‫ء‬‫ﺎ‬‫ﻛ‬‫ذ‬‫ﻟ‬‫ا‬ ‫ﺔ‬‫ﯾ‬‫ر‬‫ﻛ‬‫ﻓ‬ ‫ﺔ‬‫ﻣ‬‫ﮭ‬‫ﻣ‬ ‫ي‬‫أ‬ ‫ﺔ‬‫ﯾ‬‫د‬‫ﺄ‬‫ﺗ‬ ‫ﮫ‬‫ﻧ‬‫ﻛ‬‫ﻣ‬‫ﯾ‬ ‫ﺎ‬‫ﮭ‬‫ﺑ‬ ‫م‬‫ﺎ‬‫ﯾ‬‫ﻘ‬‫ﻟ‬‫ا‬ ‫ن‬‫ﺎ‬‫ﺳ‬‫ﻧ‬‫ﻺ‬‫ﻟ‬ ‫ن‬‫ﻛ‬‫ﻣ‬‫ﯾ‬ 3 ‫ق‬‫ﺋ‬‫ﺎ‬‫ﻔ‬‫ﻟ‬‫ا‬ ‫ﻲ‬‫ﻋ‬‫ﺎ‬‫ﻧ‬‫ط‬‫ﺻ‬‫ﻻ‬‫ا‬ ‫ء‬‫ﺎ‬‫ﻛ‬‫ذ‬‫ﻟ‬‫ا‬ ‫ل‬‫و‬‫ﻘ‬‫ﻌ‬‫ﻟ‬‫ا‬ ‫ل‬‫ﺿ‬‫ﻓ‬‫أ‬ ‫ن‬‫ﻣ‬ ‫ر‬‫ﯾ‬‫ﺛ‬‫ﻛ‬‫ﺑ‬ ‫ﻰ‬‫ﻛ‬‫ذ‬‫أ‬ ‫ر‬‫ﻛ‬‫ﻓ‬ ‫ﺎ‬‫ﺑ‬‫ﯾ‬‫ر‬‫ﻘ‬‫ﺗ‬ ‫ل‬‫ﺎ‬‫ﺟ‬‫ﻣ‬ ‫ل‬‫ﻛ‬ ‫ﻲ‬‫ﻓ‬ ‫ﺔ‬‫ﯾ‬‫ر‬‫ﺷ‬‫ﺑ‬‫ﻟ‬‫ا‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫أﻧواع‬
  • 22. https://bimarabia.com/OmarSelim/ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫ﻟﻠذﻛﺎء‬ ‫ﻣراﺣل‬ ‫ﺛﻼث‬ ‫اﻟﺿﯾق‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟﻌﺎم‬ ‫اﻟذﻛﺎء‬ ‫اﻟﺧﺎرق‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ 2020 2050 2015 ‫ﺳﻧوا‬ ‫ت‬ AGI ‫ﻟﻛن‬
  • 23. https://bimarabia.com/OmarSelim/ ‫اﻟﺿﯾق‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫اﻟﻌﺎﻧﻲ‬ 2015 AGI ASI 2020 2050 • ‫اﺻطﻧﺎﻋﯾﺔ‬ ‫أﺷﻛﺎل‬ ‫ﻣن‬ ‫ﺷﻛل‬ ‫ھﻲ‬ ‫اﻟﯾوم‬ ‫اﻟﻣطﺑﻘﺔ‬ ‫اﻷﻧظﻣﺔ‬ • ‫اﻟﺿﯾق‬ ‫اﻟذﻛﺎء‬ (ANI). • ‫واﻹﯾﻣﺎءات‬ ‫اﻷﺷﯾﺎء‬ ‫ﻋﻠﻰ‬ ‫اﻟﺗﻌرف‬ ‫ﻣﺛل‬ ‫وظﯾﻔﯾﯾن‬ ‫ﻣﺟﺎﻟﯾن‬ ‫أو‬ ‫ﻣﺟﺎل‬ ‫ﻋﻠﻰ‬ ‫ﺗﻘﺗﺻر‬ ‫وھﻲ‬. • ‫ﺷﻲء‬ ‫أي‬ ‫ﺗﺻور‬ ‫وﻻ‬ ‫ﻟذاﺗﮭﺎ‬ ‫ﻣدرﻛﺔ‬ ‫ﻟﯾﺳت‬ ‫اﻷﻧظﻣﺔ‬ ‫ھذه‬ • ‫اﻟذاﺗﻲ‬ ‫اﻟوﻋﻲ‬. • ‫ﻣﺟرد‬ ‫أﻧﮫ‬ ‫إﻻ‬ ، ‫ﯾﺑدو‬ ‫ﻣﺎ‬ ‫ﻋﻠﻰ‬ ‫اﻟﻘرارات‬ ‫ﯾﺗﺧذون‬ ‫أﻧﮭم‬ ‫ﻣن‬ ‫اﻟرﻏم‬ ‫ﻋﻠﻰ‬ ‫اﻟﺧﻠﻔﯾﺔ‬ ‫ﻓﻲ‬ ‫اﻟﻌﻣل‬ ‫أﺛﻧﺎء‬ ‫اﻟرﯾﺎﺿﯾﺎت‬ ‫أو‬ ‫اﻹﺣﺻﺎﺋﯾﺎت‬. ‫اﻟﺿﯾق‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ (ANI)
  • 24. https://bimarabia.com/OmarSelim/ ‫اﻟﺿﯾق‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫اﻟﻌﺎﻧﻲ‬ 2015 AGI ASI 2020 2050 • ‫اﻟذﻛﯾﺔ‬ ‫اﻟﮭواﺗف‬ ‫ﺗطﺑﯾﻘﺎت‬ • AlphaGo ‫و‬ ‫اﻟﺷطرﻧﺞ‬ • ‫اﻟﺻورة‬ ‫ﺗﺣدﯾد‬ ‫أدوات‬ • ‫اﻟﻛﻼم‬ ‫ﻋﻠﻰ‬ ‫اﻟﺗﻌرف‬ ‫أدوات‬ • ‫اﻟذاﺗﯾﺔ‬ ‫اﻟﻘﯾﺎدة‬ ‫أﻧظﻣﺔ‬ • ‫اﻟﻣﺗرﺟم‬ ‫ﺟوﺟل‬ • ‫اﻟﻌﺷواﺋﻲ‬ ‫اﻟﺑرﯾد‬ ‫ﻣرﺷﺣﺎت‬ ANI ‫ﻋﻠﻰ‬ ‫أﻣﺛﻠﺔ‬
  • 25. https://bimarabia.com/OmarSelim/ ‫اﻟﺿﯾق‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫اﻟﻌﺎﻧﻲ‬ 2015 ‫اﻟﺧﺎرق‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ASI 2050 ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟﻌﺎم‬ ‫اﻟذﻛﺎء‬ AGI 2020 • ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫ﺗﺳﺗﺧدم‬ ‫اﻟﺗﻲ‬ ‫اﻷﻧظﻣﺔ‬ ‫ﺗﻐطﻲ‬ ‫اﻟﺗﻔﻛﯾر‬ ‫ﻣﺛل‬ ‫وظﯾﻔﯾﺔ‬ ‫ﻣﺟﺎﻻت‬ ‫ﻣن‬ ‫أﻛﺛر‬ (AGI) ‫اﻟﻌﺎم‬ .‫اﻟﻣﺟرد‬ ‫واﻟﺗﻔﻛﯾر‬ ‫اﻟﻣﺷﻛﻼت‬ ‫وﺣل‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟﻌﺎم‬ ‫اﻟذﻛﺎء‬ (AGI)
  • 26. https://bimarabia.com/OmarSelim/ ‫اﻟﺿﯾق‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫اﻟﻌﺎﻧﻲ‬ 2015 ‫اﻟﺧﺎرق‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ASI 2050 ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟﻌﺎم‬ ‫اﻟذﻛﺎء‬ AGI 2020 ‫اﻷﻏراض‬ ‫ﻣﺗﻌددة‬ ‫أﻧظﻣﺔ‬ ‫واﻟﺗﻔﻛﯾر‬ ‫واﻟﺗﻔﻛﯾر‬ ‫اﻟذﻛﺎء‬ ‫ﻣن‬ ‫اﻟﺑﺷري‬ ‫اﻟﻣﺳﺗوى‬ ‫ذات‬ ‫اﻷﻧظﻣﺔ‬ ‫اﻟﻘرار‬ ‫واﺗﺧﺎذ‬ ‫اﻟﺗوﻟﯾف‬ ‫ﻋﻠﻰ‬ ‫اﻟﻘدرة‬ ‫ﻣﻊ‬ ‫أﻧظﻣﺔ‬ ‫اﻹﺟراءات‬ ‫ﻗرار‬ ‫واﺗﺧﺎذ‬ ‫ﻣﺗﻧوﻋﺔ‬ ‫ﻣﻌﻠوﻣﺎت‬ ‫اﻟﻌﺎم‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫ﻋﻠﻰ‬ ‫أﻣﺛﻠﺔ‬
  • 30. https://bimarabia.com/OmarSelim/ ‫اﻟﻣﺧﺗﻠﻔﺔ‬ ‫اﻟﻣﯾزات‬ ‫ﻋﻠﻰ‬ ً‫ء‬‫ﺑﻧﺎ‬ ‫اﻟﻣﺳﺎﻛن‬ ‫أﺳﻌﺎر‬ ‫ﺗوﻗﻊ‬ ‫اﻟﻐرف‬ ‫ﻋدد‬ ‫اﻟﺣﻣﺎﻣﺎت‬ ‫اﻟﺟراج‬ ‫ﻣﺳﺎﺣﺔ‬ ‫ﺑﻧﻰ‬ ‫ﻣﺗﻰ‬ ‫ﻣوﻗﻊ‬ Supervised Learning Example
  • 31. https://bimarabia.com/OmarSelim/ ‫اﻹﺷراف‬ ‫ﺗﺣت‬ ‫اﻟﺗﻌﻠم‬ ‫ﻣﻌﻧﻰ‬ ‫اﻟﻣﺗوﻗﻌﺔ‬ ‫اﻟﻘواﻋد‬ ‫أو‬ ‫اﻟﻣﺧرﺟﺎت‬ ‫ﻣﻊ‬ ‫ﺟﻧب‬ ‫إﻟﻰ‬ ‫ًﺎ‬‫ﺑ‬‫ﺟﻧ‬ ‫اﻟﺗدرﯾب‬ ‫ﺑﯾﺎﻧﺎت‬ ML ‫ﺑرﻧﺎﻣﺞ‬ ‫ﺗزوﯾد‬ ‫ﯾﺗم‬ ، ‫ﻟﻺﺷراف‬ ‫اﻟﺧﺎﺿﻊ‬ ‫اﻟﺗﻌﻠم‬ ‫ﺣﺎﻟﺔ‬ ‫ﻓﻲ‬ .‫اﻟﻣﻠﺻﻘﺎت‬ ‫ﺑﺎﺳم‬ ‫ًﺎ‬‫ﺿ‬‫أﯾ‬ ‫اﻟﻣﻌروﻓﺔ‬ ‫اﻟﺑﯾﺎﻧﺎت‬ ‫ھذه‬ ‫ﻟﺗﺻﻧﯾف‬ ‫اﻟﻣﺳﺗﻘﺑل‬ ‫ﻓﻲ‬ ‫ﺑﺎﻟﻣﺧرﺟﺎت‬ ‫ﻟﻠﺗﻧﺑؤ‬ ‫واﻟﻣﺧرﺟﺎت‬ ‫اﻟﻣدﺧﻼت‬ ‫ﻣن‬ ‫اﻟﻣﺟﻣوﻋﺔ‬ ‫ھذه‬ ML ‫ﻧظﺎم‬ ‫ﯾﺳﺗﺧدم‬ .‫اﻟﺗﺻﻧﯾف‬ ‫ﻓﻲ‬ ‫ﺟﯾد‬ ‫ﺑﺷﻛل‬ ‫ﯾﻌﻣل‬ .‫ﻣرﺋﯾﺔ‬ ‫ﻏﯾر‬ ‫ﻣدﺧﻼت‬
  • 32. https://bimarabia.com/OmarSelim/ ‫اﻹﺷراف‬ ‫ﺗﺣت‬ ‫اﻟﺗﻌﻠم‬ ‫ﻋﻣﻠﯾﺔ‬ ‫اﻟﺑﯾﺎﻧﺎت‬ ‫ادﺧﺎل‬ ‫اﻟﻣﯾزات‬ ‫ُﺗوﻗﻊ‬‫ﻣ‬ ‫اﻧﺗﺎج‬ ‫اﻟﻣﺳﻣﻰ‬ ‫اﻟﺗدرﯾب‬ ‫ﺑﯾﺎﻧﺎت‬ + ‫اﻵﻟﻲ‬ ‫اﻟﺗﻌﻠم‬ ‫ﺧوارزﻣﯾﺔ‬ ‫اﻟﻣﺗﻌﻠم‬ ‫اﻟﻧﻣوذج‬
  • 33. https://bimarabia.com/OmarSelim/ ‫ﻧﻣوذج‬ ‫اﻟﻣﻌروﻓﺔ‬ ‫اﻟﺑﯾﺎﻧﺎت‬ ‫اﺳﺗﺟﺎﺑﺔ‬ ‫ﻣﻌروﻓﺔ‬ ‫اﻟﺗﻔﺎح‬ ‫ھﻲ‬ ‫ھذه‬ ‫اﻟﻧﻣوذج‬ ‫ﺗدرﯾب‬ :‫اﻷوﻟﻰ‬ ‫اﻟﺧطوة‬ ‫ﻣﻠف‬ ‫ﻣﻊ‬ ‫ﻟﻠﺗﻔﺎح‬ ‫ا‬ً‫ﺻور‬ ‫ﻗدم‬ ‫اﻟﻣﺻﻧﻔﺔ‬ ‫اﻟﺑﯾﺎﻧﺎت‬ ‫ﯾﺳﻣﻰ‬ ‫ﻣﺎ‬ ‫وھذا‬ .‫ﻟﻠﻧﻣوذج‬ ‫اﻟﻣﺗوﻗﻌﺔ‬ ‫اﻻﺳﺗﺟﺎﺑﺔ‬. ‫ﻟﻺﺷراف‬ ‫اﻟﺧﺎﺿﻊ‬ ‫اﻟﺗﻌﻠم‬ ‫ﻣﺛﺎل‬
  • 34. https://bimarabia.com/OmarSelim/ ‫ﻧﻣوذج‬ ‫؟‬ ‫ﺑﯾﺎﻧﺎت‬ ‫ﺟدﯾدة‬ ‫اﻟﻧﻣوذج‬ ‫اﺧﺗﺑر‬ :‫اﻟﺛﺎﻧﯾﺔ‬ ‫اﻟﺧطوة‬ • ‫اﻟﻣﺻﻧﻔﺔ‬ ‫اﻟﺑﯾﺎﻧﺎت‬ ‫ﻣن‬ ‫اﻟﻧﻣوذج‬ ‫ﯾﺗﻌﻠم‬. • ‫أﺧرى‬ ‫ﻣرة‬ ‫ﻟﻠﻧﻣوذج‬ ‫اﻟﺻور‬ ‫ﻣن‬ ‫ﻣﺟﻣوﻋﺔ‬ ‫ﺑﺗوﻓﯾر‬ ‫ﻗم‬ • ‫اﻟﻣﺗوﻗﻊ‬ ‫اﻟﻧﺎﺗﺞ‬ ‫ﺑدون‬. • ‫ﺗﻔﺎﺣﺎت‬ ‫"ھذه‬ ‫ھو‬ ‫اﻟﻧﻣوذج‬ ‫"ﻧﺎﺗﺞ‬. ‫ﻟﻺﺷراف‬ ‫اﻟﺧﺎﺿﻊ‬ ‫اﻟﺗﻌﻠم‬ ‫ﻣﺛﺎل‬ ‫ﺟدﯾدة‬ ‫اﺳﺗﺟﺎﺑﺔ‬ ‫اﻟﺗﻔﺎح‬ ‫ھﻲ‬ ‫ھذه‬
  • 35. https://bimarabia.com/OmarSelim/ ‫اﻟطﻘس‬ ‫ﺗطﺑﯾﻘﺎت‬ :1 ‫ﻣﺛﺎل‬ ‫إﻟﻰ‬ ‫ﻣﻌﯾن‬ ‫وﻗت‬ ‫ﻓﻲ‬ ‫اﻟطﻘس‬ ‫ﺗطﺑﯾﻘﺎت‬ ‫ﻗدﻣﺗﮭﺎ‬ ‫اﻟﺗﻲ‬ ‫اﻟﺗﻧﺑؤات‬ ‫ﺗﺳﺗﻧد‬ ‫ﻟﻣﻛﺎن‬ ‫زﻣﻧﯾﺔ‬ ‫ﻓﺗرة‬ ‫ﻣدار‬ ‫ﻋﻠﻰ‬ ‫ﻟﻠطﻘس‬ ‫وﺗﺣﻠﯾل‬ ‫ﻣﺳﺑﻘﺔ‬ ‫ﻣﻌرﻓﺔ‬ ‫ﻣﻌﯾن‬. ‫ﻟﻺﺷراف‬ ‫اﻟﺧﺎﺿﻊ‬ ‫اﻟﺗﻌﻠم‬ ‫ﻋﻠﻰ‬ ‫أﻣﺛﻠﺔ‬
  • 38. https://bimarabia.com/OmarSelim/ Types of Supervised Learning 2 1 Classification Supervised Learning Regression In supervised learning, algorithm is selected based on target variable.
  • 39. https://bimarabia.com/OmarSelim/ ‫اﻟﺗﺻﻧﯾف‬ ‫ﺧوارزﻣﯾﺔ‬ ‫ﻓﺎﺳﺗﺧدم‬ ، (‫)ﻓﺋﺎت‬ ‫ًﺎ‬‫ﯾ‬‫ﻓﺋو‬ ‫اﻟﮭدف‬ ‫اﻟﻣﺗﻐﯾر‬ ‫ﻛﺎن‬ ‫إذا‬. (‫)ﺗﺎﺑﻊ‬ ‫ﻟﻺﺷراف‬ ‫اﻟﺧﺎﺿﻊ‬ ‫اﻟﺗﻌﻠم‬ ‫أﻧواع‬ .‫ﺳرﯾﺔ‬ ‫ﻗﯾم‬ ‫و‬ ‫ًا‬‫د‬‫ﻣﺣد‬ ‫اﻟﻧﺎﺗﺞ‬ ‫ﯾﻛون‬ ‫ﻋﻧدﻣﺎ‬ ‫اﻟﺗﺻﻧﯾف‬ ‫ﺗطﺑﯾق‬ ‫ﯾﺗم‬ ، ‫آﺧر‬ ‫ﺑﻣﻌﻧﻰ‬ ‫واﻟﻠون‬ ‫واﻟوزن‬ ‫اﻟﻣﻘطوﻋﺔ‬ ‫واﻟﻣﺳﺎﻓﺔ‬ ‫اﻟﺣﺻﺎﻧﯾﺔ‬ ‫اﻟﻘدرة‬ ‫ﻣﺛل‬ ‫ﻟﺧﺻﺎﺋﺻﮭﺎ‬ ‫ا‬ً‫ﻧظر‬ ‫اﻟﺳﯾﺎرة‬ ‫ﻓﺋﺔ‬ ‫ﺗوﻗﻊ‬ :‫ﻣﺛﺎل‬ .‫ذﻟك‬ ‫إﻟﻰ‬ ‫وﻣﺎ‬ ‫ﺳﯾﺎرات‬ ‫أو‬ ‫ﺳﯾدان‬ - ‫ﻟﻠﺗﺣﻠﯾل‬ ‫ﻣﺣﺗﻣﻠﺔ‬ ‫ﻧﺗﺎﺋﺞ‬ ‫ﺛﻼث‬ ‫ھﻧﺎك‬ .‫اﻟﻣﯾزات‬ ‫ھذه‬ ‫ﻋﻠﻰ‬ ً‫ء‬‫ﺑﻧﺎ‬ ‫ﺳﻣﺎﺗﮫ‬ ‫اﻟﻣﺻﻧف‬ ‫ﺳﯾﺑﻧﻲ‬ ‫ھﺎﺗﺷﺑﺎك‬ ‫أو‬ ‫اﻟرﺑﺎﻋﻲ‬ ‫اﻟدﻓﻊ‬ ‫ﺗﺻﻧﯾف‬ ‫ﺣرﻛﺔ‬
  • 40. https://bimarabia.com/OmarSelim/ ‫اﻻﻧﺣدار‬ ‫ﺧوارزﻣﯾﺔ‬ ‫ﻓﺎﺳﺗﺧدم‬ ، (2000-100) ‫ا‬ً‫ﻣﺳﺗﻣر‬ ‫ًﺎ‬‫ﯾ‬‫رﻗﻣ‬ ‫ا‬ً‫ﻣﺗﻐﯾر‬ ‫اﻟﮭدف‬ ‫اﻟﻣﺗﻐﯾر‬ ‫ﻛﺎن‬ ‫إذا‬. (‫)ﺗﺎﺑﻊ‬ ‫ﻟﻺﺷراف‬ ‫اﻟﺧﺎﺿﻊ‬ ‫اﻟﺗﻌﻠم‬ ‫أﻧواع‬ ‫ذﻟك‬ ‫إﻟﻰ‬ ‫وﻣﺎ‬ ‫اﻟﻧوم‬ ‫ﻏرف‬ ‫وﻋدد‬ ‫وﻣوﻗﻌﮫ‬ ‫اﻟﻣرﺑﻌﺔ‬ ‫ﻣﺳﺎﺣﺗﮫ‬ ‫إﻟﻰ‬ ‫ﺑﺎﻟﻧظر‬ ‫اﻟﻣﻧزل‬ ‫ﺳﻌر‬ ‫ﺗوﻗﻊ‬ :‫ﻣﺛﺎل‬. ‫ﺑﺳﯾطﺔ‬ ‫اﻧﺣدار‬ ‫ﺧوارزﻣﯾﺔ‬ ‫ﯾﻠﻲ‬ ‫ﻓﯾﻣﺎ‬ ‫ب‬ + ‫س‬ * ‫ث‬ = ‫ص‬ (‫)س‬ ‫اﻟﻣرﺑﻌﺔ‬ ‫واﻟﻣﺳﺎﺣﺔ‬ (‫)ص‬ ‫اﻟﺳﻌر‬ ‫ﺑﯾن‬ ‫اﻟﻌﻼﻗﺔ‬ ‫ھذا‬ ‫ﯾوﺿﺢ‬ ‫ﻣﺣدد‬ ‫ﻧطﺎق‬ ‫ﻣن‬ ‫رﻗم‬ ‫ھو‬ ‫اﻟﺳﻌر‬ ‫ﺣﯾث‬. ‫ﺗراﺟﻊ‬
  • 41. https://bimarabia.com/OmarSelim/ Types of Supervised Learning (Contd.) Classification Regression What Class ? How much ?
  • 42. https://bimarabia.com/OmarSelim/ ‫اﻟﺗﺻﻧﯾف‬ ‫ﺧوارزﻣﯾﺎت‬ ‫أﻧواع‬ ‫اﻟﺗوﻗﻊ‬ ‫ﺑﯾﺎﻧﺎت‬ ‫ﻋﻠﻰ‬ ً‫ء‬‫ﺑﻧﺎ‬ ‫اﻟﻧﺗﯾﺟﺔ‬ ‫ﻣﺗﻐﯾر‬ ‫ﺣول‬ ‫وھرﻣﯾﺔ‬ ‫ﻣﺗﺳﻠﺳﻠﺔ‬ ‫ﻗرارات‬ ‫اﻟﻘرار‬ ‫أﺷﺟﺎر‬ ‫ﺗﺗﺧذ‬ ‫اﻟﻘرار‬ ‫ﺷﺟرة‬ ‫ﻣن‬ ‫أﻓﺿل‬ ‫ودﻗﺔ‬ ‫ا‬ ً ‫ﺗﻧﺑؤ‬ ‫ﯾﻌطﻲ‬ .‫اﻟﻘرار‬ ‫أﺷﺟﺎر‬ ‫ﻣن‬ ‫ﻣﺟﻣوﻋﺔ‬ ‫ھﻲ‬ Random Forest ‫ﻣﺳﺗﻘﻠﺔ‬ ‫اﻟﻣﯾزات‬ ‫أن‬ ‫ﺑﺎﻓﺗراض‬ ‫وﯾﻌﻣل‬ ‫ﺑﺎﯾز‬ ‫ﻧظرﯾﺔ‬ ‫إﻟﻰ‬ ‫ًا‬‫د‬‫اﺳﺗﻧﺎ‬ ‫اﻹﻣﻛﺎن‬ ‫ﻗدر‬ ‫ﺑﯾﻧﮭﻣﺎ‬ ‫ﻣﺗﺑﺎﻋدة‬ ‫ﺑﮭواﻣش‬ ‫ﻣﺧﺗﻠﻔﺔ‬ ‫ﻓﺋﺎت‬ ‫إﻟﻰ‬ ‫اﻟﻣﺛﯾﻼت‬ ‫ﺗﻔﺻل‬ ‫اﻟﺗﻲ‬ ‫اﻟﻣﯾزة‬ ‫ﻣﺳﺎﺣﺔ‬ ‫ﻓﻲ‬ ‫اﻟﻔﺎﺋق‬ ‫اﻟﻣﺳﺗوى‬ SVM ‫ﯾرﺳم‬ ‫ﻣﻌﯾﻧﺔ‬ ‫ﻣﺟﻣوﻋﺔ‬ ‫ﻋﻠﻰ‬ ً‫ء‬‫ﺑﻧﺎ‬ (‫ﺧطﺄ‬ / ‫ﺻواب‬ ، ‫ﻻ‬ / ‫ﻧﻌم‬ ، 0/1 ‫ﻣﺛل‬ ‫اﻟﺛﻧﺎﺋﯾﺔ‬ ‫)اﻟﻘﯾم‬ ‫اﻟﻣﻧﻔﺻﻠﺔ‬ ‫اﻟﻘﯾم‬ ‫ﻟﺗﻘدﯾر‬ ‫ﺗﺳﺗﺧدم‬ ‫اﻟﻣﺳﺗﻘﻠﺔ‬ ‫اﻟﻣﺗﻐﯾرات‬ ‫ﻣن‬ ‫اﻟﻘرار‬ ‫أﺷﺟﺎر‬ ‫ﻋﺷواﺋﯾﺔ‬ ‫ﻏﺎﺑﺔ‬ ‫ﺑﺎﯾز‬ ‫ﻣﺻﻧف‬ ‫اﻟﻣﺗﺟﮭﺎت‬ ‫آﻻت‬ ‫دﻋم‬ ‫اﻟﻠوﺟﺳﺗﻲ‬ ‫اﻻﻧﺣدار‬
  • 43. https://bimarabia.com/OmarSelim/ ‫اﻟﻛﻼﺳﯾﻛﻲ‬ ‫اﻵﻟﺔ‬ ‫ّم‬ ‫ﻠ‬ ‫ﺗﻌ‬ ‫ﻟﻺﺷراف‬ ‫اﻟﺧﺎﺿﻊ‬ ‫ّم‬‫ﻠ‬‫اﻟﺗﻌ‬ ‫ﻟﻺﺷراف‬ ‫اﻟﺧﺎﺿﻊ‬ ‫ﻏﯾر‬ ‫ّم‬‫ﻠ‬‫اﻟﺗﻌ‬ ‫اﻟﺗﺻﻧﯾف‬ (Classification) ‫اﻻﻧﺣدار‬ (Regression) ‫اﻟﺗﺟﻣﯾﻊ‬ (Clustering). ‫اﻟﺗﻌﻣﯾم‬ ‫أو‬ ‫اﻷﺑﻌﺎد‬ ‫ﺗﻘﻠﯾل‬ (Dimensionality Reduction) ‫اﻟرﺑط‬ ‫ﻗواﻋد‬ ‫ﺗﻌﻠم‬ (Association rule learning).
  • 44. https://bimarabia.com/OmarSelim/ Unsupervised Learning vs. Supervised Learning , Training Text Documents, Images, etc. Feature Vectors Machine Learning Algorithm New Text, Document, Images, etc. Feature Vectors Predictive Model Likelihood or Cluster ID or Better Representation Labels , Training Text Documents, Images, etc. Feature Vectors Machine Learning Algorithm New Text, Document, Images, etc. Feature Vectors Predictive Model Expected Label The only difference is the labels in the training data
  • 46. https://bimarabia.com/OmarSelim/ ‫ﻟﻺﺷراف‬ ‫اﻟﺧﺎﺿﻊ‬ ‫ﻏﯾر‬ ‫اﻟﺗﻌﻠم‬ ‫ﺗطﺑﯾق‬ 0 2 4 6 8 10 -2 -1 0 1 2 3 4 5 6 7 ‫اﻟﺗﺷﺎﺑﮫ‬ ‫أوﺟﮫ‬ ‫ﺗﺣدﯾد‬ ‫اﻟﻣﺟﻣوﻋﺎت‬ ‫ﻓﻲ‬ (Clustering) 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.9 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 0.1 + + + + + + + + ++ + +++ + x x x x x xx x x x x x x x x x xx 0.0251 0.0033 0.008 0.0119 Anomaly detection Unsupervised learning can be used for anomaly detection as well as clustering
  • 47. https://bimarabia.com/OmarSelim/ ‫ﻟﻺﺷراف‬ ‫اﻟﺧﺎﺿﻊ‬ ‫ﻏﯾر‬ ‫اﻟﺗﻌﻠم‬ ‫ﻣﻌﻧﻰ‬ • ‫ﻓﻘط‬ ‫اﻹدﺧﺎل‬ ‫ﺑﯾﺎﻧﺎت‬ ‫اﺳﺗﺧدام‬ ‫ﯾﺗم‬ .‫ﻣﺳﻣﺎة‬ ‫ﻏﯾر‬ ‫ﺑﯾﺎﻧﺎت‬ ‫ﻣﺟﻣوﻋﺔ‬ ‫ﻣن‬ ‫اﻵﻟﻲ‬ ‫اﻟﺗﻌﻠم‬ ‫ﺧوارزﻣﯾﺔ‬ ‫ﺗﺗﻌﻠم‬ ، ‫ﻟﻺﺷراف‬ ‫اﻟﺧﺎﺿﻊ‬ ‫ﻏﯾر‬ ‫اﻟﺗﻌﻠم‬ ‫ﺣﺎﻟﺔ‬ ‫ﻓﻲ‬ ‫اﻟﻧﻣوذج‬ ‫ﻟﺗدرﯾب‬ ‫اﻟﺧوارزﻣﯾﺔ‬ ‫ﺑواﺳطﺔ‬. • ‫ھذه‬ ‫اﻹدﺧﺎل‬ ‫ﺑﯾﺎﻧﺎت‬ ‫ﻣن‬ ‫ﺷﺎذة‬ ‫وﺣﺎﻻت‬ ‫ًﺎ‬‫ط‬‫أﻧﻣﺎ‬ ‫اﻟﺧوارزﻣﯾﺔ‬ ‫ﺗﺟد‬ ‫أن‬ ‫اﻟﻣﺗوﻗﻊ‬ ‫ﻣن‬. • ‫اﻟﻣﻐﻧﺎطﯾﺳﻲ‬ ‫ﺑﺎﻟرﻧﯾن‬ ‫اﻟﺗﺻوﯾر‬ ‫وﺗﺣﻠﯾل‬ ‫اﻟﻌﻣﻼء‬ ‫وﺗﺟزﺋﺔ‬ ‫اﻻﺣﺗﯾﺎل‬ ‫ﻋن‬ ‫اﻟﻛﺷف‬ ‫ﻓﻲ‬ ‫اﻟﻐﺎﻟب‬ ‫ﻓﻲ‬ ‫اﻟطرﯾﻘﺔ‬ ‫ھذه‬ ‫ُﺳﺗﺧدم‬‫ﺗ‬.
  • 48. https://bimarabia.com/OmarSelim/ ‫ﻟﻺﺷراف‬ ‫اﻟﺧﺎﺿﻌﺔ‬ ‫ﻏﯾر‬ ‫اﻟﺗﻌﻠم‬ ‫ﻋﻣﻠﯾﺔ‬ ‫اﻟﺗدرﯾب‬ ‫ﺑﯾﺎﻧﺎت‬ ‫ﺑﯾﺎﻧﺎت‬ ‫ﻣﯾزات‬ ‫اﻹدﺧﺎل‬ ‫اﻵﻟﻲ‬ ‫اﻟﺗﻌﻠم‬ ‫ﺧوارزﻣﯾﺔ‬ ‫اﻟﻣﺗﻌﻠم‬ ‫اﻟﻧﻣوذج‬
  • 49. https://bimarabia.com/OmarSelim/ ‫ﻧﻣوذج‬ ‫ﻣﻌروف‬ ‫ﺑﯾﺎﻧﺎت‬ ‫اﻟﺻورة‬ ‫ﺗﻌرﯾف‬ :‫ﻟﻺﺷراف‬ ‫اﻟﺧﺎﺿﻊ‬ ‫ﻏﯾر‬ ‫اﻟﺗﻌﻠم‬ ‫ﻣﺛﺎل‬ ‫اﻟﻣﺳﻣﺎة‬ ‫ﻏﯾر‬ ‫اﻟﺑﯾﺎﻧﺎت‬ ‫إدﺧﺎل‬ :‫اﻷوﻟﻰ‬ ‫اﻟﺧطوة‬ ‫ﻋﻠﻰ‬ ‫ﺗﺣﺗوي‬ ‫اﻟﺗﻲ‬ ‫ﺑﺎﻟﺑﯾﺎﻧﺎت‬ ‫اﻟﻧظﺎم‬ ‫ﻧزود‬ ‫ﻧﺣن‬ ‫ﺑدون‬ ‫اﻟﻔﺎﻛﮭﺔ‬ ‫ﻣن‬ ‫ﻣﺧﺗﻠﻔﺔ‬ ‫ﺑﺄﻧواع‬ ‫ﺻور‬ ‫اﻟﻣﺳﻣﺎة‬ ‫ﻏﯾر‬ ‫اﻟﺑﯾﺎﻧﺎت‬ ‫ﯾﺳﻣﻰ‬ ‫ﻣﺎ‬ ‫وھذا‬ .‫اﻟﻣﺗوﻗﻊ‬ ‫اﻟﻧﺎﺗﺞ‬. ‫اﻟﺑﯾﺎﻧﺎت‬ ‫ﻣﺧرﺟﺎت‬ ‫ﻓﮭم‬ ‫ھو‬ ‫ﻟﻺﺷراف‬ ‫اﻟﺧﺎﺿﻌﺔ‬ ‫ﻏﯾر‬ ‫اﻟﺗﻌﻠم‬ ‫ﻧﻣﺎذج‬ ‫ﻣن‬ ‫اﻟﮭدف‬ ‫اﻟﻣﻌﯾﻧﺔ‬ ‫واﻹﺷﻌﺎرات‬ ‫اﻟﺗﺷﺎﺑﮫ‬ ‫وأوﺟﮫ‬ ‫واﻻﺗﺟﺎھﺎت‬ ‫اﻷﻧﻣﺎط‬.
  • 50. https://bimarabia.com/OmarSelim/ ‫ﻧﻣوذج‬ ‫اﻟﺑﯾﺎﻧﺎت‬ ‫اﻟﻣﻌروﻓﺔ‬ ‫ﻣرﺋﻲ‬ ‫ﻧﻣط‬ ‫اﻟﻧﻣوذج‬ ‫ﺗدرﯾب‬ :‫اﻟﺛﺎﻧﯾﺔ‬ ‫اﻟﺧطوة‬ • ‫اﻟﺑﯾﺎﻧﺎت‬ ‫ﻓﻲ‬ ‫واﻟﺣﺟم‬ ‫واﻟﻠون‬ ‫اﻟﺷﻛل‬ ‫ﻣﺛل‬ ‫اﻷﻧﻣﺎط‬ ‫اﻟﻧﻣوذج‬ ‫ﯾﺣدد‬. • ‫اﻟﺻﻔﺎت‬ ‫أو‬ ‫اﻟﺻﻔﺎت‬ ‫أو‬ ‫اﻟﻣﯾزات‬ ‫ھذه‬ ‫ﻋﻠﻰ‬ ً‫ء‬‫ﺑﻧﺎ‬ ‫اﻟﺛﻣﺎر‬ ‫ﺑﺗﺟﻣﯾﻊ‬ ‫ﯾﻘوم‬. ‫اﻟﺻورة‬ ‫ﺗﻌرﯾف‬ :‫ﻟﻺﺷراف‬ ‫اﻟﺧﺎﺿﻊ‬ ‫ﻏﯾر‬ ‫اﻟﺗﻌﻠم‬ ‫ﻣﺛﺎل‬
  • 51. https://bimarabia.com/OmarSelim/ ‫اﻟﻣﺎوس‬ ‫ﻧﻘرات‬ :‫ﻟﻺﺷراف‬ ‫اﻟﺧﺎﺿﻊ‬ ‫ﻏﯾر‬ ‫اﻟﺗﻌﻠم‬ ‫ﻣﺛﺎل‬ • ‫أ‬ ‫ﻋﻠﻰ‬ ‫اﻟﻣﺎوس‬ ‫ﻧﻘرات‬ ‫ﻟﻔﮭم‬ ‫ﻟﻺﺷراف‬ ‫اﻟﺧﺎﺿﻊ‬ ‫ﻏﯾر‬ ‫اﻟﺗﻌﻠم‬ ‫اﺳﺗﺧدام‬ ‫ﯾﺗم‬ • ‫وﯾب‬ ‫ﻣوﻗﻊ‬ ‫أو‬ ‫وﯾب‬ ‫ﺻﻔﺣﺔ‬. • ‫اﻟﻣﺳﺗﺧدم‬ ‫ﺗﺻﻔﺢ‬ ‫أﻧﻣﺎط‬ ‫ﻓﮭم‬ ‫ﻋﻠﻰ‬ ‫اﻟﺷرﻛﺎت‬ ‫ﯾﺳﺎﻋد‬.
  • 52. https://bimarabia.com/OmarSelim/ ‫ﻟﻺﺷراف‬ ‫اﻟﺧﺎﺿﻊ‬ ‫ﺷﺑﮫ‬ ‫اﻟﺗﻌﻠم‬ ‫ﻣﻌﻧﻰ‬ • ‫ﻟﻺﺷراف‬ ‫اﻟﺧﺎﺿﻊ‬ ‫اﻟﺗﻌﻠم‬ ‫ﻣن‬ ‫ﻣزﯾﺞ‬ ‫وھو‬ ‫ھﺟﯾن‬ ‫ﻧﮭﺞ‬ ‫ھو‬ ‫ﻟﻺﺷراف‬ ‫اﻟﺧﺎﺿﻊ‬ ‫ﺷﺑﮫ‬ ‫اﻟﺗﻌﻠم‬ ‫ﻟﻺﺷراف‬ ‫اﻟﺧﺎﺿﻊ‬ ‫ﻏﯾر‬ ‫واﻟﺗﻌﻠم‬. • ‫اﻟﻣﺳﻣﺎة‬ ‫وﻏﯾر‬ ‫اﻟﻣﺻﻧﻔﺔ‬ ‫اﻟﺑﯾﺎﻧﺎت‬ ‫ﻣن‬ ‫ﻣﺟﻣوﻋﺔ‬ ‫ﯾﺳﺗﺧدم‬.
  • 53. https://bimarabia.com/OmarSelim/ ‫ﻟﻺﺷراف‬ ‫اﻟﺧﺎﺿﻊ‬ ‫ﺷﺑﮫ‬ ‫اﻟﺗﻌﻠم‬ ‫ﻣﺛﺎل‬ • ‫وﺗﺟﻣﯾﻌﮭﺎ‬ ‫اﻟﺑﯾﺎﻧﺎت‬ ‫ﺟﻣﻊ‬ :‫اﻷوﻟﻰ‬ ‫اﻟﺧطوة‬ • ‫اﻟﻣﺻﻧﻔﺔ‬ ‫وﻏﯾر‬ ‫اﻟﻣﺻﻧﻔﺔ‬ ‫اﻟﺑﯾﺎﻧﺎت‬ ‫ﺟﻣﻊ‬ ‫ﻟﻠﺗدرﯾب‬ ‫وﺗﺟﻣﯾﻌﮭﺎ‬. ‫اﻟﻣﺻﻧﻔﺔ‬ ‫اﻟﺑﯾﺎﻧﺎت‬ ‫ﻣﺻﻧﻔﺔ‬ ‫ﻏﯾر‬ ‫ﺑﯾﺎﻧﺎت‬ ‫اﻟﺗدرﯾب‬ ‫ﺑﯾﺎﻧﺎت‬
  • 54. https://bimarabia.com/OmarSelim/ ‫اﻟﺧﺎﺿﻊ‬ ‫ﺷﺑﮫ‬ ‫اﻟﺗﻌﻠم‬ ‫ﻣﺛﺎل‬ ‫ﻟﻺﺷراف‬ • ‫اﻟﺑﯾﺎﻧﺎت‬ ‫إدﺧﺎل‬ :‫اﻟﺛﺎﻧﯾﺔ‬ ‫اﻟﺧطوة‬ • ‫اﻟﻧﻣوذج‬ ‫ﻓﻲ‬ ‫اﻟﺗدرﯾب‬ ‫ﺑﯾﺎﻧﺎت‬ ‫ﺟﻣﯾﻊ‬ ‫ﺑﺗﻐذﯾﺔ‬ ‫ﻗم‬. ‫اﻟﺗدرﯾب‬ ‫ﺑﯾﺎﻧﺎت‬ ‫ﻧﻣوذج‬
  • 55. https://bimarabia.com/OmarSelim/ ،Machine Learning ‫اﻵﻟﺔ‬ ‫ﱡم‬‫ﻠ‬‫ﺗﻌ‬ ‫ﻋﻠﻰ‬ ‫اﻟﻘﺎﺋﻣﺔ‬ (AL) ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫ﻋﻠم‬ ‫ﻋن‬ ‫اﻟﻣﻧﺑﺛﻘﺔ‬ ‫اﻟﻔروع‬ ‫أﺣد‬ ‫ﺑﺄﻧﮫ‬ ‫اﻵﻟﺔ‬ ‫ﱡم‬‫ﻠ‬‫ﺗﻌ‬ ‫ﻣﻔﮭوم‬ ‫ﺗﺑﺳﯾط‬ ‫ﯾﻣﻛن‬ ،ML ‫ﺑـ‬ ‫ا‬ً‫اﺧﺗﺻﺎر‬ ‫ﻟﮫ‬ ‫ُﺷﺎر‬‫ﯾ‬‫و‬ ‫اﻟﻣﺗوﻓرة‬ ‫اﻟﺑﯾﺎﻧﺎت‬ ‫ﻋﻠﻰ‬ ‫ﺑﺎﻻﻋﺗﻣﺎد‬ ‫إﻟﯾﮭﺎ‬ ‫اﻟﻣوﻛوﻟﺔ‬ ‫اﻷواﻣر‬ ‫وﺗﻧﻔﯾذ‬ ‫اﻟﻣﮭﺎم‬ ‫أداء‬ ‫ﻋﻠﻰ‬ ‫ﻗﺎدرة‬ ‫ﻟﺗﺻﺑﺢ‬ ‫أﺷﻛﺎﻟﮭﺎ‬ ‫ﺑﻣﺧﺗﻠف‬ ‫اﻟﺣواﺳﯾب‬ ‫ﺑرﻣﺟﺔ‬ ‫راﺋد‬ ‫ﻣن‬ ٍ‫ﺑﺈﯾﻌﺎز‬ ‫ظﮭر‬ ‫ﻗد‬ ‫اﻵﻟﺔ‬ ‫ﺗﻌﻠم‬ ‫ﻣﺻطﻠﺢ‬ ‫أن‬ ‫إﻟﻰ‬ ‫وﯾﺷﺎر‬ .‫ًﺎ‬‫ﻣ‬‫ﺗﻣﺎ‬ ‫ﺗﻐﯾﯾﺑﮫ‬ ‫أو‬ ‫ﺗوﺟﯾﮭﮭﺎ‬ ‫ﻓﻲ‬ ‫اﻟﺑﺷري‬ ‫اﻟﺗدﺧل‬ ‫ﺗﻘﯾﯾد‬ ‫ﻣﻊ‬ ‫وﺗﺣﻠﯾﻠﮭﺎ‬ ‫ﻟدﯾﮭﺎ‬ ‫ﻓﻲ‬ ‫اﻵﻟﺔ‬ ‫ﻓﺈن‬ ‫ﺑﺎﻟذﻛر‬ ِ‫اﻟﺟدﯾر‬ ‫وﻣن‬ ،IBM ‫ﻣﺧﺗﺑرات‬ ‫ﻋﻣل‬ ِ‫ﻧطﺎق‬ ‫ﺿﻣن‬ 1959 ‫ﺳﻧﺔ‬ ‫ﻓﻲ‬ Arthur Samuel ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫اﻟﻌﻧﺻر‬ ‫دور‬ ‫ﻓﯾﻛون‬ ،‫ﻣﻧﮭﺎ‬ ‫اﻟﻣطﻠوﺑﺔ‬ ‫واﻟﻣﮭﺎم‬ ‫اﻷواﻣر‬ ‫ﻟﻣواﺟﮭﺔ‬ ‫ًﺎ‬‫ﻘ‬‫ﻣﺳﺑ‬ ‫إﻟﯾﮭﺎ‬ ‫اﻟﻣدﺧﻠﺔ‬ ‫اﻟﺑﯾﺎﻧﺎت‬ ‫ﺗﺣﻠﯾل‬ ‫ﻋﻠﻰ‬ ‫ﺗﻌﺗﻣد‬ ‫أن‬ ‫ﯾﺟب‬ ‫اﻟﺣﺎﻟﺔ‬ ‫ھذه‬ .‫اﻟﻣطﺎف‬ ‫ﻧﮭﺎﯾﺔ‬ ‫ﻓﻲ‬ ‫ًا‬‫د‬‫ﺟ‬ ً ‫ﺿﺋﯾﻼ‬ ‫اﻟﺑﺷري‬ ‫ﻟﻶﻻت‬ ‫ﯾﻣﻛن‬ ،‫اﻟواﻗﻊ‬ ‫وﻓﻲ‬ .‫دﻗﯾق‬ ‫ﻏﯾر‬ ‫اﻻﻋﺗﻘﺎد‬ ‫ھذا‬ ‫أن‬ ‫إﻻ‬ ،‫اﺻطﻧﺎﻋﯾﺎ‬ ‫ذﻛﺎء‬ ‫اﻵﻟﻲ‬ ‫اﻟﺗﻌﻠم‬ ‫ﯾﻌﺗﺑرون‬ ‫اﻟﻧﺎس‬ ‫ﻣﻌظم‬ ‫أن‬ ‫ﻣن‬ ‫اﻟرﻏم‬ ‫وﻋﻠﻰ‬ .‫ﻟﮭﺎ‬ ‫اﻟﻣﻘدﻣﺔ‬ ‫اﻟﺑﯾﺎﻧﺎت‬ ‫ﻣن‬ ‫ﺗﺗﻌﻠم‬ ‫أن‬ ‫ﻟﻠروﺑوﺗﺎت‬ ‫ﯾﻣﻛن‬ ‫ﻛﻣﺎ‬ ،‫ﺗﺗﻌﻠم‬ ‫أن‬ ‫ﺛم‬ ‫واﻟﺗﻌﻠم‬ ‫اﻟﺑﯾﺎﻧﺎت‬ ‫ﻋﻠﻰ‬ ‫ﻟﻠﺣﺻول‬ ‫اﻟﺧوارزﻣﯾﺎت‬ ‫ﺗﺳﺗﺧدم‬ ‫ﺣﯾث‬ ،‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫وﺟود‬ ‫ﻧدرك‬ ‫ﺗﺟﻌﻠﻧﺎ‬ ‫ﺗﻘﻧﯾﺔ‬ ‫إﯾﺟﺎد‬ ‫ﺗم‬ ،‫اﻟﺣﻘﯾﻘﺔ‬ ‫ﻓﻲ‬ ‫أو‬ ‫ﺟوﺟل‬ ‫أو‬ ‫اﻟﺗﺳوق‬ ‫ﻣواﻗﻊ‬ ‫ﻣن‬ ‫ﺗوﺻﯾﺔ‬ ‫ﻋﻠﻰ‬ ‫ﺣﺻوﻟك‬ ‫ﻋﻧد‬ ‫ﯾﺗﺟﻠﻰ‬ ‫ذﻟك‬ ‫أن‬ ‫ﺑﺎﻟذﻛر‬ ‫واﻟﺟدﯾر‬ .‫ﺗﻧﺑؤات‬ ‫ﺷﻛل‬ ‫ﻋﻠﻰ‬ ‫اﻟﻧﺗﺎﺋﺞ‬ ‫ﻟﺗﺄﺗﻲ‬ ،‫اﻟﺗﺣﻠﯾل‬ ‫ﺗطوﯾرھﺎ‬ ‫ﺗم‬ ‫اﻟﺗﻲ‬ ‫اﻵﻟﻲ‬ ‫اﻟﺗﻌﻠم‬ ‫ﺧوارزﻣﯾﺎت‬ ‫ﺑﺎﺳﺗﺧدام‬ ‫ذﻟك‬ ‫ﯾﺗم‬ ‫ﻛﻣﺎ‬ .‫اھﺗﻣﺎﻣﺎﺗك‬ ‫ﻣﻊ‬ ‫ﺗﺗواﻓق‬ ‫اﻗﺗراﺣﺎت‬ ‫ﻋﻠﻰ‬ ‫اﻟﺣﺻول‬ ‫ﯾﻣﻛﻧك‬ ‫إذ‬ ،‫ﻓﯾﺳﺑوك‬ ‫ﻗطﺎﻋﻲ‬ ‫ﻋﻠﻰ‬ ‫ًﺎ‬‫ﺿ‬‫أﯾ‬ ‫ﺗؤﺛر‬ ‫اﻟﺗﻘﻧﯾﺔ‬ ‫ھذه‬ ‫ﺑﺎن‬ ‫اﻟﺗﻧوﯾﮫ‬ ‫ﻣن‬ ‫ﺑد‬ ‫وﻻ‬ .‫اﻷﺧرى‬ ‫اﻟﻣﻌﻠوﻣﺎت‬ ‫ﻣن‬ ‫واﻟﻌدﯾد‬ ‫واﻟﺗﺎرﯾﺦ‬ ‫اﻟﺣدﯾﺛﺔ‬ ‫اﻟﺑﺣث‬ ‫ﻋﻣﻠﯾﺎت‬ ‫ﻟﺗﺣﻠﯾل‬ .‫واﻟﺑﻧوك‬ ‫اﻟﺗﺳوﯾق‬ ."‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫ﯾﺟﺳد‬ ‫ﻛﻣﺎ‬ ،‫اﻟﺑﯾﺎﻧﺎت‬ ‫ﺗﺣﻠﯾل‬ ‫ﻣن‬ ‫اﻟﺗﻌﻠم‬ ‫ﻋﻠﻰ‬ ‫اﻵﻻت‬ ‫ﻗدرة‬ ‫اﻵﻟﻲ‬ ‫اﻟﺗﻌﻠم‬ ‫"ﯾﺷﻛل‬ ‫ًا‬‫ء‬‫ﺟز‬ ‫اﻟراھن‬ ‫اﻟوﻗت‬ ‫ﻓﻲ‬ ‫أﺻﺑﺣت‬ ‫ﻟﻛﻧﮭﺎ‬ ،‫اﻷﺳﺎﺳﯾﺔ‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫ﻣﻘوﻣﺎت‬ ‫ﻋﻠﻰ‬ ‫اﻟﺟدﯾدة‬ ‫اﻵﻟﻲ‬ ‫اﻟﺗﻌﻠم‬ ‫ﺧوارزﻣﯾﺎت‬ ‫اﻗﺗﺻرت‬ ‫ﻓﻲ‬ ‫ﻧﻘﻠﺔ‬ ‫اﻵﻟﻲ‬ ‫اﻟﺗﻌﻠم‬ ‫ﺣﻘق‬ ‫ﻓﻘد‬ .‫أﻓﺿل‬ ‫ﺗﺟرﺑﺔ‬ ‫اﻟﻣﺳﺗﺧدﻣﯾن‬ ‫ﻟﻣﻧﺢ‬ ‫اﻟﻣﻌﻘدة‬ ‫اﻟﺧوارزﻣﯾﺎت‬ ‫ﻣن‬ ‫اﻟﻌدﯾد‬ ‫اﺑﺗﻛﺎر‬ ‫وﯾﺗم‬ .‫اﻟﻧظﺎم‬ ‫ھذا‬ ‫ﻣن‬ ‫ﺟوھرﯾﺎ‬ ‫اﻟوﯾب‬ ‫ﻗﻧوات‬ ‫ﻋﻠﻰ‬ ‫ﻟﻣﺷﺎھدﯾﮭﺎ‬ ‫ﻣﻧﺎﺳﺑﺔ‬ ‫اﻗﺗراﺣﺎت‬ ‫ﻟﺗﻘدﯾم‬ ‫اﻟﺧوارزﻣﯾﺔ‬ ‫ھذه‬ ‫اﻟﺗرﻓﯾﮫ‬ ‫ﺻﻧﺎﻋﺔ‬ ‫وﺗﺳﺗﺧدم‬ .‫واﻷﻓﻼم‬ ‫اﻟﻌروض‬ ‫ﻣﺷﺎھدة‬ ‫طرﯾﻘﺔ‬ ‫ﺗﻠك‬ ‫ﻣن‬ ‫اﻟﺗﻌﻠم‬ ‫إﻟﻰ‬ ‫ﺗﺳﺗﻧد‬ ‫ﻣﻣﺗﺎزة‬ ‫ﺗوﺻﯾﺎت‬ ‫وﯾﻘدم‬ ‫اﻟﺑﯾﺎﻧﺎت‬ ‫اﻵﻟﻲ‬ ‫اﻟﺗﻌﻠم‬ ‫ﯾﺣﻠل‬ ،‫ذﻟك‬ ‫ﻋن‬ ‫ﻓﺿﻼ‬ ."‫ﺑراﯾم‬ ‫و"أﻣﺎزون‬ "‫"ﻧﯾﺗﻔﻠﯾﻛس‬ ‫ﻣﺛل‬
  • 56. https://bimarabia.com/OmarSelim/ ‫اﻟﺑﯾﺎﻧﺎت‬ ‫ﻋﻠوم‬ ‫ﻣن‬ ‫واﻟﺗﻘﻧﯾﺎت‬ ‫اﻟﻧظرﯾﺎت‬ ‫ﻣن‬ ‫ًا‬‫د‬‫ﻋد‬ ‫اﻵﻟﻲ‬ ‫اﻟﺗﻌﻠم‬ ‫ﯾﺳﺗﺧدم‬: ‫اﻻﻟﻲ‬ ‫اﻟﺗﻌﻠم‬ ‫اﻟﻘرار‬ ‫ﺻﻧﺎﻋﺔ‬ ‫اﻟﺗﺻﻧﯾف‬ ‫ﺧﻠﻘﻲ‬ ‫ﻋﯾب‬ ‫إﻛﺗﺷﺎف‬ ‫ﺗﺻﻧﯾف‬ ‫ﺗﺟﻣﻊ‬ ‫اﻟﺗﺻور‬ 6 7 1 2 3 4 ‫اﻻﺗﺟﺎه‬ ‫ﺗﺣﻠﯾل‬ 5 ‫اﻵﻟﻲ‬ ‫اﻟﺗﻌﻠم‬ ‫ﺗﻘﻧﯾﺎت‬
  • 57. https://bimarabia.com/OmarSelim/ Machine Learning Decision making Categorization Anomaly detection Classification Clustering Visualization 6 7 1 2 3 4 Trend analysis 5 Machine Learning Techniques ‫ﻓﯾﮭﺎ‬ ‫ﯾﺗﻌﻠم‬ ‫ﺗﻘﻧﯾﺔ‬ ‫ﻋن‬ ‫ﻋﺑﺎرة‬ ‫اﻟﺗﺻﻧﯾف‬ ‫اﻟﺑﯾﺎﻧﺎت‬ ‫إدﺧﺎل‬ ‫ﻣن‬ ‫اﻟﻛﻣﺑﯾوﺗر‬ ‫ﺑرﻧﺎﻣﺞ‬ ‫ﯾﺳﺗﺧدﻣﮭﺎ‬ ‫ﺛم‬ ‫ﻟﮫ‬ ‫اﻟﻣﻌطﻰ‬ ‫اﻟﺟدﯾدة‬ ‫اﻟﻣﻼﺣظﺔ‬ ‫ﻟﺗﺻﻧﯾف‬ ‫اﻟﺗﻌﻠم‬ ‫ھذا‬
  • 58. https://bimarabia.com/OmarSelim/ Machine Learning Decision making Anomaly detection Classification Visualization 6 7 1 3 4 Trend analysis 5 Machine Learning Techniques 2 Categorization ‫ﻓﺋﺎت‬ ‫إﻟﻰ‬ ‫اﻟﺑﯾﺎﻧﺎت‬ ‫ﻟﺗﻧظﯾم‬ ‫ﺗﻘﻧﯾﺔ‬ ‫وﻛﻔﺎءة‬ ‫ﻓﻌﺎﻟﯾﺔ‬ ‫اﻷﻛﺛر‬ ‫ﻻﺳﺗﺧداﻣﮭﺎ‬. Clustering
  • 59. https://bimarabia.com/OmarSelim/ Machine Learning Decision making Categorization Anomaly detection Classification Visualization 6 7 1 2 3 4 Trend analysis 5 Machine Learning Techniques Clustering ‫ﺗﺟﻣﻊ‬ ‫ﺗﺟﻌل‬ ‫ﺑطرﯾﻘﺔ‬ ‫اﻟﻛﺎﺋﻧﺎت‬ ‫ﻣن‬ ‫ﻣﺟﻣوﻋﺔ‬ ‫ﺗﺟﻣﯾﻊ‬ ‫ﺗﻘﻧﯾﺔ‬ ‫أﻛﺛر‬ ‫اﻟﻣﺟﻣوﻋﺔ‬ ‫ﻧﻔس‬ ‫ﻓﻲ‬ ‫اﻟﻣوﺟودة‬ ‫اﻟﻛﺎﺋﻧﺎت‬ ‫اﻟﻣوﺟودة‬ ‫ﺗﻠك‬ ‫ﻣن‬ ‫أﻛﺛر‬ ‫اﻟﺑﻌض‬ ‫ﺑﻌﺿﮭﺎ‬ ‫ﻣﻊ‬ ‫ًﺎ‬‫ﮭ‬‫ﺗﺷﺎﺑ‬ ‫اﻷﺧرى‬ ‫اﻟﻣﺟﻣوﻋﺎت‬ ‫ﻓﻲ‬
  • 60. https://bimarabia.com/OmarSelim/ Machine Learning Decision making Categorization Anomaly detection Classification Clustering Visualization 6 7 1 2 3 4 Trend analysis 5 Machine Learning Techniques Trend Analysis is a technique aimed at projecting both current and future movement of events through use of time series data analysis
  • 61. https://bimarabia.com/OmarSelim/ Machine Learning Decision making Categorization Anomaly detection Classification Clustering Visualization 6 7 1 2 3 4 Trend analysis 5 Machine Learning Techniques Anomaly detection is a technique to identify cases that are unusual within data that is seemingly homogeneous
  • 62. https://bimarabia.com/OmarSelim/ Machine Learning Decision making Categorization Anomaly detection Classification Clustering Visualization 6 7 1 2 3 4 Trend analysis 5 Machine Learning Techniques Technique to present data in a pictorial or graphical format. It enables decision makers to see analytics presented visually
  • 63. https://bimarabia.com/OmarSelim/ Machine Learning Decision making Categorization Anomaly detection Classification Clustering Visualization 6 7 1 2 3 4 Trend analysis 5 Machine Learning Techniques A technique/skill which provides you with the ability to influence managerial decisions with data as evidence for those possibilities
  • 64. https://bimarabia.com/OmarSelim/ (Deep Learning) ‫اﻟﻌﻣﯾق‬ ‫ّم‬‫ﻠ‬‫اﻟﺗﻌ‬ ‫أو‬ ‫ّق‬‫ﻣ‬‫ُﺗﻌ‬‫ﻣ‬‫اﻟ‬ ‫ّم‬‫ﻠ‬‫اﻟﺗﻌ‬ ‫ﻣﺣﺎﻛﺎة‬ ‫طرﯾق‬ ‫ﻋن‬ ‫ﺑﻧﻔﺳﮭﺎ‬ ‫ﺗﺗﻌﻠم‬ ‫أن‬ ‫ﻟﻶﻟﺔ‬ ‫ﺗﺗﯾﺢ‬ ‫وﺧوارزﻣﯾﺎت‬ ‫ﻧظرﯾﺎت‬ ‫إﯾﺟﺎد‬ ‫ﯾﺗﻧﺎول‬ ‫ﺟدﯾد‬ ‫ﺑﺣث‬ ‫ﻣﺟﺎل‬ ‫ھو‬ ‫ﻓروع‬ ‫ﻣن‬ ‫ﻓرع‬ ‫ُﯾﻌد‬ ،‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫ﻋﻠوم‬ ‫ﺗﺗﻧﺎول‬ ‫اﻟﺗﻲ‬ ‫اﻟﻌﻠوم‬ ‫ﻓروع‬ ‫أﺣد‬ ‫و‬ ،‫اﻹﻧﺳﺎن‬ ‫ﺟﺳم‬ ‫ﻓﻲ‬ ‫اﻟﻌﺻﺑﯾﺔ‬ ‫اﻟﺧﻼﯾﺎ‬ ‫ﺑﺗﺣﻠﯾل‬ ‫اﻟﻣﺗﺟردات‬ ‫ﻣن‬ ‫ﻋﺎﻟﯾﺔ‬ ‫درﺟﺔ‬ ‫اﺳﺗﻧﺑﺎط‬ ‫أﺳﺎﻟﯾب‬ ‫إﯾﺟﺎد‬ ‫ﻋﻠﻰ‬ ‫اﻟﻣﺗﻌﻣق‬ ‫اﻟﺗﻌﻠم‬ ‫أﺑﺣﺎث‬ ‫ﻣﻌظم‬ ‫ﺗرﻛز‬ ،‫اﻵﻟﻲ‬ ‫اﻟﺗﻌﻠم‬ ‫ﻋﻠوم‬ .‫ﺧطﯾﺔ‬ ‫وﻏﯾر‬ ‫ﺧطﯾﺔ‬ ‫ﻣﺗﺣوﻻت‬ ‫ﺑﺎﺳﺗﺧدام‬ ‫ﺿﺧﻣﺔ‬ ‫ﺑﯾﺎﻧﺎت‬ ‫ﻣﺟﻣوﻋﺔ‬ ‫اﻟﺗﻌﻠم‬ ‫أﻧظﻣﺔ‬ ‫ﻣن‬ ‫ﻓرﻋﯾﺔ‬ ‫ﻣﺟﻣوﻋﺔ‬ ‫ﻣن‬ ‫اﻟﻌﻣﯾق‬ ‫اﻟﺗﻌﻠم‬ ‫ﯾﺗﻛون‬ ،‫اﻟواﻗﻊ‬ ‫وﻓﻲ‬ .‫اﻵﻟﻲ‬ ‫اﻟﺗﻌﻠم‬ ‫ﻧظﺎم‬ ‫ﺗﻧﻔﯾذ‬ ‫ﻓﻲ‬ ‫اﻟﻌﻣﯾق‬ ‫اﻟﺗﻌﻠم‬ ‫ﯾﺗﺟﺳد‬ ‫ﻓﻲ‬ ‫اﻵﻟﻲ‬ ‫اﻟﺗﻌﻠم‬ ‫ﻧظﺎم‬ ‫اﻟﺗﻘﻧﯾﺔ‬ ‫ھذه‬ ‫وﺗﺷﺑﮫ‬ .‫اﻵﻻت‬ ‫ﺗﻣﻠﻛﮭﺎ‬ ‫اﻟﺗﻲ‬ ‫اﻟﺗﺷﻐﯾل‬ ‫ﻗدرات‬ ‫ﺗﺷﻛل‬ ‫اﻟﺗﻲ‬ ،‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫ﻣن‬ ‫أو‬ ،‫اﻵﻟﻲ‬ ‫اﻟﺗﻌﻠم‬ ‫ﯾﺳﺗطﯾﻊ‬ ‫ﺣﯾن‬ ‫ﻓﻲ‬ ،‫اﻟﻣﮭﻣﺔ‬ ‫ﻷداء‬ ‫اﻟﺗوﺟﯾﮭﺎت‬ ‫ﺑﻌض‬ ‫إﻟﻰ‬ ‫ﯾﺣﺗﺎج‬ ‫اﻵﻟﻲ‬ ‫اﻟﺗﻌﻠم‬ ‫أن‬ ‫ﻓﻲ‬ ‫اﻟﻔرق‬ ‫ﯾﻛﻣن‬ ‫وﻟﻛن‬ ،‫اﻟﺳﯾﺎﻗﺎت‬ ‫ﺑﻌض‬ ‫اﺳﺗﺧﻼص‬ ‫ﯾﻛﻣن‬ ‫ﺣﯾث‬ ،‫اﻟﻣﺳﺗﺧدﻣﯾن‬ ‫ﺧﺑرة‬ ‫اﻟﻌﻣﯾق‬ ‫اﻟﺗﻌﻠم‬ ‫ﻋزز‬ ،‫ذﻟك‬ ‫إﻟﻰ‬ ‫ﺑﺎﻹﺿﺎﻓﺔ‬ .‫اﻟﻣﺑرﻣﺞ‬ ‫ﺗدﺧل‬ ‫دون‬ ‫اﻟﻣﮭﻣﺔ‬ ‫أداء‬ ‫اﻟﻌﻣﯾق‬ .‫اﻷوﺗوﻣﺎﺗﯾﻛﯾﺔ‬ ‫اﻟﺳﯾﺎرة‬ ‫ﺧﺎﺻﯾﺎت‬ ‫ﺧﻼل‬ ‫ﻣن‬ ‫اﻟﻌﻣﯾق‬ ‫ﻟﻠﺗﻌﻠم‬ ‫ﻧﻣوذج‬ ‫أﻓﺿل‬ ."‫اﻟﻌﻣﯾق‬ ‫ﺑﺎﻟﺗﻌﻠم‬ ‫اﻵﻟﻲ‬ ‫اﻟﺗﻌﻠم‬ ‫ﻟﺗﻧﻔﯾذ‬ ‫اﻟﻣﺳﺗﺧدﻣﺔ‬ ‫اﻟﺗﻘﻧﯾﺔ‬ ‫"ﺗﻌرف‬ ‫إﺻﻼح‬ ‫اﻟﻣﺑرﻣﺟﯾن‬ ‫ﻋﻠﻰ‬ ‫ﯾﻧﺑﻐﻲ‬ ،‫اﻵﻟﻲ‬ ‫اﻟﺗﻌﻠم‬ ‫ﻧظﺎم‬ ‫ﻣﻊ‬ ‫اﻟﺗﻌﺎﻣل‬ ‫وﻋﻧد‬ .‫اﻟﺑﺷر‬ ‫ﻣﺛل‬ ‫وﺗﻔﻛر‬ ‫ﺗﻌﻣل‬ ‫اﻵﻻت‬ ‫اﻟﻌﻣﯾق‬ ‫اﻟﺗﻌﻠم‬ ‫ﺟﻌل‬ ‫اﻟﻌﻘل‬ ‫ﻣﺛل‬ ‫ًﺎ‬‫ﻣ‬‫ﺗﻣﺎ‬ ،‫ﺑﻧﻔﺳﮭﺎ‬ ‫ﺑذﻟك‬ ‫ﺗﺗﻛﻔل‬ ‫ﻓﺈﻧﮭﺎ‬ ،‫اﻟﻌﻣﯾق‬ ‫اﻟﺗﻌﻠم‬ ‫ﻟﻧﻣﺎذج‬ ‫ﺑﺎﻟﻧﺳﺑﺔ‬ ‫ﻟﻛن‬ ،‫ﻣﻧﺎﺳﺑﺔ‬ ‫ﻏﯾر‬ ‫اﻟﻧﺗﺎﺋﺞ‬ ‫ﻛﺎﻧت‬ ‫ﻣﺎ‬ ‫إذا‬ ‫اﻟﺧوارزﻣﯾﺔ‬ .‫اﻟﺑﺷري‬ ‫اﻵﻟﻲ‬ ‫اﻟﺗﻌﻠم‬ ‫ﺧوارزﻣﯾﺔ‬ ‫ﺳﺗﻘوم‬ ‫ذﻟك‬ ‫ﻋﻧد‬ ،"‫"اﺷﺗﻐل‬ ‫ﺑﻛﻠﻣﺔ‬ ‫اﻟﻣﺷﻐل‬ ‫ﯾﻧطق‬ ‫ﻋﻧدﻣﺎ‬ ‫ﻟﯾﻧطﻠق‬ ‫ﻟﻠﻣروﺣﺔ‬ ‫رﻣز‬ ‫ﺑﺿﺑط‬ ‫ﻗﻣت‬ ‫أﻧك‬ ‫ﺗﺧﯾل‬ ‫ﺣﺗﻰ‬ ‫اﻟﻣروﺣﺔ‬ ‫ﺗﻌﻣل‬ ‫ﻓﻠن‬ ،‫اﻟدﻗﯾﻘﺔ‬ ‫اﻟﻛﻠﻣﺔ‬ ‫ﻋﻠﻰ‬ ‫ﺗﺣﺻل‬ ‫ﻟم‬ ‫وإذا‬ ."‫"اﺷﺗﻐل‬ ‫ﻛﻠﻣﺔ‬ ‫ﻋن‬ ‫واﻟﺑﺣث‬ ‫ﺑﺄﻛﻣﻠﮭﺎ‬ ‫اﻟﻣﺣﺎدﺛﺔ‬ ‫إﻟﻰ‬ ‫ﺑﺎﻻﺳﺗﻣﺎع‬ ‫ﻟدرﺟﺔ‬ ‫ًا‬‫د‬‫ﺟ‬ ‫ﺳﺎﺧﻧﺔ‬ ‫"اﻟﻐرﻓﺔ‬ :‫ﻗﻠت‬ ‫ﻟو‬ ‫ﺣﺗﻰ‬ ‫اﻟﻣروﺣﺔ‬ ‫اﻟﻌﻣﯾق‬ ‫اﻟﺗﻌﻠم‬ ‫ﻧﻣوذج‬ ‫ﺳﯾﺷﻐل‬ ،‫أﺧرى‬ ‫ﻧﺎﺣﯾﺔ‬ ‫ﻣن‬ .‫ذﻟك‬ ‫ﺗرﯾد‬ ‫ﻛﻧت‬ ‫إذا‬ ‫ﻧﻔﺳﮫ‬ ‫اﻟﻌﻣﯾق‬ ‫اﻟﺗﻌﻠم‬ ‫ﯾﻠﻘن‬ ‫أن‬ ‫ﯾﻣﻛن‬ ‫إذ‬ ،‫ﻣﺧﺗﻠﻔﯾن‬ ‫اﻟﻧظﺎﻣﯾن‬ ‫ﻛﻼ‬ ‫اﻷﺳﺎﺳﯾﺔ‬ ‫اﻟﻧﻘﺎط‬ ‫ھذه‬ ‫ﺗﺟﻌل‬ ،‫اﻟﻌﻣوم‬ ‫وﻋﻠﻰ‬ ."‫ﻓﯾﮭﺎ‬ ‫اﻟﺑﻘﺎء‬ ‫ﯾﺻﻌب‬ .‫ﻣﺣدد‬ ‫ﺑرﻧﺎﻣﺞ‬ ‫ﺑواﺳطﺔ‬ ‫ﺗﺷﻐﯾﻠﮫ‬ ‫إﻟﻰ‬ ‫اﻵﻟﻲ‬ ‫اﻟﺗﻌﻠم‬ ‫ﯾﺣﺗﺎج‬ ‫ﺑﯾﻧﻣﺎ‬ ،‫ﺑﻧﻔﺳﮫ‬ https://www.naftaliharris.com/ blog/visualizing-dbscan-clust ering/ https://www.youtube.com/wat ch?v=Lu56xVlZ40M https://www.youtube.com/wat ch?v=CqYKhbyHFtA
  • 65. https://bimarabia.com/OmarSelim/ ‫رﻣز‬ ‫ﻛﺗﺎﺑﺔ‬ ‫دون‬ ‫اﻵﻟﺔ‬ ‫ﺗﻌﻠم‬ ‫ﻧﻣﺎذج‬ ‫اﺧﺗﺑﺎر‬ :What-If ‫أداة‬
  • 71. https://bimarabia.com/OmarSelim/ Reinforcement‫اﻟﻣﻌزز‬ ‫اﻟﺗﻌﻠم‬ ‫ﻣﻌﻧﻰ‬ • ‫اﻟﺳﻠوك‬ ‫وﺗﻌﻠم‬ ‫اﻟﺑﯾﺋﺔ‬ ‫ﺑﻣراﻗﺑﺔ‬ ‫اﻟﺗﻌﻠم‬ ‫ﻟﻧظﺎم‬ ‫ﯾﺳﻣﺢ‬ ‫اﻟذي‬ ‫اﻵﻟﻲ‬ ‫اﻟﺗﻌﻠم‬ ‫ﻣن‬ ‫ﻧوع‬ ‫ھو‬ ‫اﻟﻣﻌزز‬ ‫اﻟﺗﻌﻠم‬ .‫اﻟﻣﺛﺎﻟﻲ‬ • ‫ﻓﻲ‬ ‫ﻣﻛﺎﻓﺂت‬ ‫ﻋﻠﻰ‬ ‫وﯾﺣﺻل‬ ‫ﻣﻌﯾﻧﺔ‬ ‫إﺟراءات‬ ‫وﯾﺗﺧذ‬ ‫وﯾﺧﺗﺎر‬ ‫اﻟﺑﯾﺋﺔ‬ (‫)اﻟوﻛﯾل‬ ‫اﻟﺗﻌﻠم‬ ‫ﻧظﺎم‬ ‫ﯾراﻗب‬ .(‫ﻣﻌﯾﻧﺔ‬ ‫ﺣﺎﻻت‬ ‫ﻓﻲ‬ ‫ﻋﻘوﺑﺎت‬ ‫)أو‬ ‫اﻟﻣﻘﺎﺑل‬ • .‫ﺣﻠﻘﺔ‬ ‫ﻓﻲ‬ ‫اﻟوﻛﯾل‬ ‫أو‬ ‫اﻟﻧظﺎم‬ ‫إﻟﻰ‬ ‫اﻟﻣﻼﺣظﺎت‬ ‫ﺗﻘدﯾم‬ ‫ﯾﺗم‬ • ‫ﺑﻣرور‬ ‫ﻣﻛﺎﻓﺂﺗﮭﺎ‬ ‫ﻣن‬ ‫ﺗزﯾد‬ ‫اﻟﺗﻲ‬ (‫اﻹﺟراءات‬ ‫)اﺧﺗﯾﺎر‬ ‫اﻟﺳﯾﺎﺳﺔ‬ ‫أو‬ ‫اﻻﺳﺗراﺗﯾﺟﯾﺔ‬ ‫اﻟوﻛﯾل‬ ‫ﯾﺗﻌﻠم‬ .‫اﻟﺗراﻛﻣﯾﺔ‬ ‫اﻟﻣﻛﺎﻓﺄة‬ ‫ﺗﻌظﯾم‬ ‫وﺗﺣﺎول‬ ‫اﻟوﻗت‬
  • 72. https://bimarabia.com/OmarSelim/ • ‫ﺑـ‬ ‫اﻟﺗﻼﻋب‬ ‫ﯾﺣﺎول‬ ‫وﻛﯾل‬ ‫ھو‬ ‫اﻟروﺑوت‬ • ‫اﻟﺳطﺢ‬ ‫ھﻲ‬ ‫اﻟﺗﻲ‬ ‫اﻟﺑﯾﺋﺔ‬. • ‫أﺧرى‬ ‫إﻟﻰ‬ ‫ﺣﺎﻟﺔ‬ ‫ﻣن‬ ‫اﻻﻧﺗﻘﺎل‬ ‫وﯾﺣﺎول‬ ‫اﻟروﺑوت‬ ‫ﯾﻣﺷﻲ‬ ‫ﻋﻧدﻣﺎ‬ ‫ھذا‬ ‫ﯾﺣدث‬. • (‫ﺧطوﺗﯾن‬ ‫)اﺗﺧﺎذ‬ ‫ﻟﻠﻣﮭﻣﺔ‬ ‫ﻓرﻋﯾﺔ‬ ‫وﺣدة‬ ‫ﻹﻧﺟﺎز‬ ‫ﻣﻛﺎﻓﺄة‬ ‫ﻋﻠﻰ‬ ‫ﯾﺣﺻل‬. ‫إﻧﺳﺎن‬ ‫آﻟﻲ‬ ‫ﺳطﺢ‬ ‫ﺟﺎﺋزة‬ ‫اﻟﻣﺷﻲ‬ ‫اﻟروﺑوت‬ :‫اﻟﻣﻌزز‬ ‫اﻟﺗﻌﻠم‬ ‫ﻣﺛﺎل‬
  • 73. https://bimarabia.com/OmarSelim/ • ‫ﻣن‬ ‫ﺟﮭﺎز‬ ‫ﻟﺗﺣدﯾد‬ ‫اﻟﻌﻣﯾق‬ ‫اﻟﺗﻌزﯾزي‬ ‫اﻟﺗﻌﻠم‬ ‫اﻟروﺑوت‬ ‫ﯾﺳﺗﺧدم‬ ، ‫اﻟﺗﺻﻧﯾﻊ‬ ‫وﺣدة‬ ‫ﻓﻲ‬ ‫ﺣﺎوﯾﺔ‬ ‫ﻓﻲ‬ ‫ووﺿﻌﮫ‬ ‫واﺣد‬ ‫ﺻﻧدوق‬. • ‫ﯾﺣﻔزه‬ ‫واﻟذي‬ ، ‫اﻟﻣﻛﺎﻓﺂت‬ ‫ﻋﻠﻰ‬ ‫اﻟﻘﺎﺋم‬ ‫اﻟﺗﻌﻠم‬ ‫ﻧظﺎم‬ ‫طرﯾق‬ ‫ﻋن‬ ‫ھذا‬ ‫اﻟروﺑوت‬ ‫ﯾﺗﻌﻠم‬ ‫اﻟﺻﺣﯾﺢ‬ ‫اﻹﺟراء‬ ‫ﻋﻠﻰ‬. ‫اﻟروﺑوت‬ :‫اﻟﻣﻌزز‬ ‫اﻟﺗﻌﻠم‬ ‫ﻣﺛﺎل‬
  • 74. https://bimarabia.com/OmarSelim/ ‫اﻟﺣﺎﺳب‬ ‫ﻣن‬ ‫أﻓﺿل‬ ‫اﻹﻧﺳﺎن‬ ‫ﯾؤدﯾﮫ‬ ‫ﻣﺎ‬ ⚫ ‫ﺑﺴﺮﻋﺔ‬ ‫اﻟﻤﻌﻠﻮﻣﺎت‬ ‫واﻛﺘﺴﺎب‬ ‫اﻟﺘﻌﻠﻢ‬ ‫ﻋﻠﻰ‬ ‫اﻟﻘﺪرة‬ ⚫ ‫واﻟﻌﻘﻠﻲ‬ ‫اﻟﺤﺴﻲ‬ ‫اﻹدراك‬ ‫ﻋﻠﻰ‬ ‫ﺑﻨﺎء‬ ‫اﻟﺼﺤﯿﺤﺔ‬ ‫اﻟﻘﺮارات‬ ‫اﺗﺨﺎذ‬ ‫ﻋﻠﻰ‬ ‫اﻟﻘﺪرة‬ ‫اﻟﻤﺸﻜﻠﺔ‬ ‫ﻟﺠﻮاﻧﺐ‬ ⚫ ‫وﺗﺼﺤﯿﺤﮭﺎ‬ ‫اﻷﺧﻄﺎء‬ ‫اﻛﺘﺸﺎف‬ ‫ﻋﻠﻰ‬ ‫اﻟﻘﺪرة‬ ⚫ ‫ﺟﺪﯾﺪة‬ ‫ﻣﻮاﻗﻒ‬ ‫إﻟﻰ‬ ‫اﻟﺬاﺗﯿﺔ‬ ‫واﻟﺨﺒﺮة‬ ‫اﻟﺘﺠﺮﺑﺔ‬ ‫ﻧﻘﻞ‬ ⚫ ‫اﻟﻤﺨﺘﻠﻔﺔ‬ ‫اﻟﻤﻌﺮﻓﺔ‬ ‫أﻧﻮاع‬ ‫ﺑﯿﻦ‬ ‫اﻟﺘﻤﯿﯿﺰ‬ ⚫ ( ‫ﻣﻼﺣﻈﺔ‬ ‫اﺑﺪاع‬ ‫ﺣﺴﯿﺔ‬ ) ‫ﺑﺎﻟﻔﻄﺮة‬ ‫واﻟﻤﮭﺎرات‬ ‫اﻟﻘﺪرات‬
  • 75. https://bimarabia.com/OmarSelim/ :‫اﻻﻧﺳﺎن‬ ‫ﻣن‬ ‫اﻓﺿل‬ ‫اﻟﺣﺎﺳب‬ ‫ﯾؤدﯾﮫ‬ ‫ﻣﺎ‬ ⚫ ‫ﺑﺎﻻﻧﺴﺎن‬ ‫ﻣﻘﺎرﻧﺔ‬ ‫ﺛﻮان‬ ‫ﻓﻲ‬ ‫اﻟﻤﻌﻘﺪة‬ ‫اﻟﺤﺴﺎﺑﯿﺔ‬ ‫اﻟﻌﻤﻠﯿﺎت‬ ‫ﻣﻦ‬ ‫ﺑﺎﻟﻌﺪﯾﺪ‬ ‫اﻟﻘﯿﺎم‬ ⚫ ‫اﻟﺘﻜﺮارﯾﺔ‬ ‫اﻷﻋﻤﺎل‬ ‫ﺧﺎﺻﺔ‬ ‫ﻣﻠﻞ‬ ‫أو‬ ‫ﻛﻠﻞ‬ ‫دون‬ ‫اﻟﻤﮭﺎم‬ ‫ﺗﻨﻔﯿﺬ‬ ⚫ ‫ﻋﺎﻟﯿﺔ‬ ‫وﻛﻔﺎءة‬ ‫ﺗﺎﻣﺔ‬ ‫ﺑﺴﺮﻋﺔ‬ ‫اﻟﻤﻌﻠﻮﻣﺎت‬ ‫ﻣﻦ‬ ‫ھﺎﺋﻞ‬ ‫ﻛﻢ‬ ‫واﺳﺘﺮﺟﺎع‬ ‫ﺗﺨﺰﯾﻦ‬ ⚫ ‫اﻻﻧﺴﺎن‬ ‫ﻣﻦ‬ ‫ﺑﺪﻻ‬ ‫اﻟﺤﺎﺳﺐ‬ ‫اﺳﺘﺨﺪام‬ ‫ﺣﺎﻟﺔ‬ ‫ﻓﻲ‬ ‫ﺑﺎﻟﻌﻤﻞ‬ ‫اﻟﺨﺎﺻﺔ‬ ‫اﻟﻨﻔﻘﺎت‬ ‫ﺗﻮﻓﺮ‬
  • 76. https://bimarabia.com/OmarSelim/ Dendral ‫ﻧظﺎم‬ ‫اﻟﻣﺳﺎﺋل‬ ‫ﺣل‬ ‫أﻧظﻣﺔ‬ ‫ﻓﻲ‬ ‫اﻟﻘﺻور‬ ‫ﻟﻣﻌﺎﻟﺟﺔ‬ ‫اﻟﻌﺎﻟم‬ ‫ﻓﻲ‬ ‫ﺧﺑﯾر‬ ‫ﻧظﺎم‬ ‫أول‬ ‫ظﮭر‬ ‫اﻟﺳﺑﻌﯾﻧﺎت‬ ‫ﻓﻲ‬ ‫أطﻠق‬ ‫ﻣن‬ ‫أول‬ ‫وھو‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫ﺑﻣﺳﺗﻘﺑل‬ ‫ﺗﻧﺑﺄ‬ ‫اﺳﯾﻣوف‬ ‫اﻟﻛﯾﻣﯾﺎﺋﻲ‬ ‫ﻟﻠﺗﺣﻠﯾل‬ ‫ﺧﺑﯾر‬ ‫ﻧظﺎم‬: 1971 ‫اﻵﻟﯾﯾن‬ ‫اﻟرﺟﺎل‬ ‫ﻋﻠﻰ‬ ‫روﺑوت‬ ‫ﻣﺻطﻠﺢ‬ ‫اﻵﻟﯾﯾن‬ ‫اﻟرﺟﺎل‬ ‫ﻟﺿﺑط‬ ‫ﻗواﻋد‬ 3 ‫وﺿﻊ‬ ‫ﺻﺎﻧﻌﯾﮭﺎ‬ ‫ﻋﻠﻰ‬ ‫اﻵﻻت‬ ‫اﻧﻘﻼب‬ ‫ﺑﻔﻛرة‬ ‫ﺗﻧﺑﺄ‬ .1 .‫ﻟﮫ‬ ‫ًى‬‫ذ‬‫أ‬ ‫ﯾﺳﺑب‬ ‫ﻗد‬ ‫ﻋﻣﺎ‬ ‫اﻟﺳﻛوت‬ ‫أو‬ ّ‫ﺑﺷري‬ ‫إﯾذاء‬ ‫آﻟﻲ‬ ‫ﯾﺟوز‬ ‫ﻻ‬ .2 .‫اﻷول‬ ‫اﻟﻘﺎﻧون‬ ‫ﻣﻊ‬ ‫ﺗﻌﺎرﺿت‬ ‫إن‬ ‫إﻻ‬ ‫اﻟﺑﺷر‬ ‫أواﻣر‬ ‫إطﺎﻋﺔ‬ ‫آﻟﻲ‬ ‫ﻋﻠﻰ‬ ‫ﯾﺟب‬ .3 .‫واﻟﺛﺎﻧﻲ‬ ‫اﻷول‬ ‫اﻟﻘﺎﻧوﻧﯾن‬ ‫ﻣﻊ‬ ‫ذﻟك‬ ‫ﯾﺗﻌﺎرض‬ ‫ﻻ‬ ‫طﺎﻟﻣﺎ‬ ‫ﺑﻘﺎﺋﮫ‬ ‫ﻋﻠﻰ‬ ‫اﻟﻣﺣﺎﻓظﺔ‬ ‫آﻟﻲ‬ ‫ﻋﻠﻰ‬ ‫ﯾﺟب‬ ‫ﯾؤذي‬ ‫أن‬ ‫روﺑوت‬ ‫ﻻي‬ ‫ﯾﻧﺑﻐﻲ‬ ‫ﻻ‬ :‫وھو‬ ،‫اﻟﻘواﻧﯾن‬ ‫ﻣﺟﻣوﻋﺔ‬ ‫إﻟﻰ‬ ‫ﺻﻔر‬ ‫اﻟﻘﺎﻧون‬ ‫أﺳﯾﻣوف‬ ‫أﺿﺎف‬ ً‫ﺎ‬‫ﻻﺣﻘ‬ ‫ﻓﻌل‬ ‫رد‬ ‫ﺑﺄي‬ ‫اﻟﻘﯾﺎم‬ ‫ﺑﻌدم‬ ‫ﻧﻔﺳﮭﺎ‬ ‫ﺑﺈﯾذاء‬ ‫اﻹﻧﺳﺎﻧﯾﺔ‬ ‫ﯾﺳﻣﺢ‬ ‫أن‬ ‫أو‬،‫اﻹﻧﺳﺎﻧﯾﺔ‬
  • 77. https://bimarabia.com/OmarSelim/ ‫أ‬ (Artificial Neural Network ANN ) ‫اﻻﺻطﻧﺎﻋﯾﺔ‬ ‫اﻟﻌﺻﺑوﻧﯾﺔ‬ ‫اﻟﺷﺑﻛﺎت‬ ‫ﻣن‬ ‫ﻣﺗراﺑطﺔ‬ ‫ﻣﺟﻣوﻋﺔ‬ : SNN ‫أو‬ simulated neural network ‫اﻟﻣﺣﺎﻛﯾﺔ‬ ‫اﻟﻌﺻﺑوﻧﯾﺔ‬ ‫ﺑﺎﻟﺷﺑﻛﺎت‬ ‫أﯾﺿﺎ‬ ‫ﯾدﻋﻰ‬ ‫ﻣﺎ‬ ‫و‬ ‫إﻟﻛﺗروﻧﯾﺔ‬ ‫ﺑﻧﻰ‬ ‫أو‬ ‫اﻟﺑﯾوﻟوﺟﻲ‬ ‫اﻟﻌﺻﺑون‬ ‫ﻋﻣل‬ ‫ﻟﺗﺷﺎﺑﮫ‬ ُ‫ﺔ‬‫ﱠ‬‫ﯾ‬‫ﺣﺎﺳوﺑ‬ ٌ‫ﺞ‬‫ﺑراﻣ‬ ‫ﺗﻧﺷﺋﮭﺎ‬ ‫اﻓﺗراﺿﯾﺔ‬ ‫اﻟﻌﺻﺑﯾﺔ‬ ‫اﻟﺧﻠﯾﺔ‬ ‫ﻋﺻﺑوﻧﺎت‬ ‫اﻟطرﯾﻘﺔ‬ ‫ﻋﻠﻰ‬ ‫ﺑﻧﺎء‬ ‫اﻟﻣﻌﻠوﻣﺎت‬ ‫ﻟﻣﻌﺎﻟﺟﺔ‬ ‫اﻟرﯾﺎﺿﻲ‬ ‫اﻟﻧﻣوذج‬ ‫ﺗﺳﺗﺧدم‬ (‫اﻟﻌﺻﺑوﻧﺎت‬ ‫ﻋﻣل‬ ‫ﻟﻣﺣﺎﻛﺎة‬ ‫ﻣﺻﻣﻣﺔ‬ ‫إﻟﻛﺗروﻧﯾﺔ‬ ‫)ﺷﯾﺑﺎت‬ ‫اﻟﺳﻠوك‬ ‫ﻟﻛن‬ ‫ﺑﺳﯾط‬ ‫ﺑﻌﻣل‬ ‫ﺗﻘوم‬ ‫ﺑﺳﯾطﺔ‬ ‫ﻣﻌﺎﻟﺟﺔ‬ ‫ﻋﻧﺎﺻر‬ ‫ﻋﺎم‬ ‫ﺑﺷﻛل‬ ‫اﻟﻌﺻﺑوﻧﯾﺔ‬ ‫اﻟﺷﺑﻛﺎت‬ ‫ﺗﺗﺄﻟف‬ .‫اﻟﺣوﺳﺑﺔ‬ ‫ﻓﻲ‬ ‫اﻻﺗﺻﺎﻟﯾﺔ‬ ‫اﻟﻌﻧﺎﺻر‬ ‫ھذه‬ ‫وﻣؤﺷرات‬ ‫ﺑﺎﻟﻌﺻﺑوﻧﺎت‬ ‫ھﻧﺎ‬ ‫ﺗدﻋﻰ‬ ‫اﻟﺗﻲ‬ ‫اﻟﻌﻧﺎﺻر‬ ‫ھذه‬ ‫ﻣﺧﺗﻠف‬ ‫ﺑﯾن‬ ‫اﻻﺗﺻﺎﻻت‬ ‫ﺧﻼل‬ ‫ﻣن‬ ‫ﯾﺗﺣدد‬ ‫ﻟﻠﺷﺑﻛﺔ‬ ‫اﻟﻛﻠﻲ‬ ‫اﻟﺗﻲ‬ ‫اﻟدﻣﺎﻏﯾﺔ‬ ‫اﻟﻌﺻﺑوﻧﺎت‬ ‫ﻋﻣل‬ ‫آﻟﯾﺔ‬ ‫ﻣن‬ ‫أﺗﻰ‬ ‫اﻟﻌﺻﺑوﻧﯾﺔ‬ ‫اﻟﺷﺑﻛﺎت‬ ‫ﺑﻔﻛرة‬ ‫اﻷول‬ ‫اﻹﯾﺣﺎء‬ .element parameters ‫أن‬ ‫ھب‬ ‫دوﻧﺎﻟد‬ ‫اﻗﺗرح‬ ‫اﻟﺷﺑﻛﺎت‬ ‫ھذه‬ ‫ﻓﻲ‬ .‫اﻟدﻣﺎغ‬ ‫إﻟﻰ‬ ‫اﻟواردة‬ ‫اﻟﻣﻌﻠوﻣﺎت‬ ‫ﻟﻣﻌﺎﻟﺟﺔ‬ ‫ﻛﮭرﺑﺎﺋﯾﺔ‬ ‫ﺑﯾوﻟوﺟﯾﺔ‬ ‫ﺑﺷﺑﻛﺎت‬ ‫ﺗﺷﺑﯾﮭﮭﺎ‬ ‫ﯾﻣﻛن‬ ‫واﻟﺷﺑﻛﺎت‬ ‫اﻻﺗﺻﺎﻟﯾﺔ‬ ‫ﻓﻛرة‬ ‫ﻓﻲ‬ ‫ﻟﻠﺗﻔﻛﯾر‬ ‫دﻓﻊ‬ ‫ﻣﺎ‬ ‫وھذا‬ ‫اﻟﻣﻌﺎﻟﺟﺔ‬ ‫ﻋﻣﻠﯾﺔ‬ ‫ﺗوﺟﯾﮫ‬ ‫ﻓﻲ‬ ‫أﺳﺎﺳﯾﺎ‬ ‫دورا‬ ‫ﯾﻠﻌب‬ ‫اﻟﻌﺻﺑﻲ‬ ‫اﻟﻣﺷﺑك‬ ‫ﻋﺻﺑوﻧﺎت‬ ‫اﻧﮫ‬ ‫ﻣﺳﺑﻘﺎ‬ ‫ذﻛرﻧﺎ‬ ‫ﻗد‬ ‫ﻣﺎ‬ ‫أو‬ ‫ﻋﻘد‬ ‫ﻣن‬ ‫اﻻﺻطﻧﺎﻋﯾﺔ‬ ‫اﻟﻌﺻﺑوﻧﯾﺔ‬ ‫اﻟﺷﺑﻛﺎت‬ ‫ﺗﺗﺎﻟف‬ .‫اﻻﺻطﻧﺎﻋﯾﺔ‬ ‫اﻟﻌﺻﺑوﻧﯾﺔ‬ ‫ھذه‬ ‫ﺑﯾن‬ ‫اﺗﺻﺎل‬ ‫وﻛل‬ ،‫اﻟﻌﻘد‬ ‫ﻣن‬ ‫ﺷﺑﻛﺔ‬ ‫ﻟﺗﺷﻛل‬ ‫ﻣﻌﺎ‬ ‫ﻣﺗﺻﻠﺔ‬ ،processing elements ‫ﻣﻌﺎﻟﺟﺔ‬ ‫وﺣدات‬ ‫أو‬ neurons ‫اﻟداﺧﻠﺔ‬ ‫اﻟﻘﯾم‬ ‫ﻋﻠﻰ‬ ‫ﺑﻧﺎء‬ ‫ﻣﻌﺎﻟﺟﺔ‬ ‫ﻋﻧﺻر‬ ‫ﻛل‬ ‫ﻋن‬ ‫اﻟﻧﺎﺗﺟﺔ‬ ‫اﻟﻘﯾم‬ ‫ﺗﺣدﯾد‬ ‫ﻓﻲ‬ ‫ﺗﺳﮭم‬ ‫اﻷوزان‬ ‫ﺗدﻋﻰ‬ ‫اﻟﻘﯾم‬ ‫ﻣن‬ ‫ﻣﺟﻣوﻋﺔ‬ ‫ﯾﻣﻠك‬ ‫اﻟﻌﻘد‬ .‫اﻟﻌﻧﺻر‬ ‫ﻟﮭذا‬
  • 78. ML Algorithms: Artificial Neural Network Source: https://www.intechopen.com/source/html/39067/media/image1.png A) human neuron; B) artificial neuron; C) biological synapse; D) ANN synapses
  • 79. https://bimarabia.com/OmarSelim/ Nicolas ‫اﻟﻣﻌﻣﺎري‬ ‫اﻟﻣﮭﻧدس‬ ‫طرﺣﮫ‬ ‫أن‬ ‫ﻣﻧذ‬ ً‫ﻼ‬‫طوﯾ‬ ‫ًﺎ‬‫ط‬‫ﺷو‬ ‫اﻟﻛﻣﺑﯾوﺗر‬ ‫ﺑﻣﺳﺎﻋدة‬ ‫ﻟﻠﺗﺻﻣﯾم‬ (AI) ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫ﻗطﻊ‬ ‫ﻟﻘد‬ .‫اﻵﻟﻲ‬ ‫اﻟﺗﻌﻠم‬ ‫ﺧوارزﻣﯾﺎت‬ ‫ﻋﻠﻰ‬ ‫اﻟﺗﻛﻧوﻟوﺟﯾﺔ‬ ‫اﻟﺗطورات‬ ‫ﻣن‬ ‫اﻟﻌدﯾد‬ ‫ﺗﻌﺗﻣد‬ .‫اﻟﺳﺑﻌﯾﻧﯾﺎت‬ ‫ﻓﻲ‬ ‫ﻧﯾﻐروﺑوﻧﺗﻲ‬ ‫ﻧﯾﻛوﻻس‬ Negroponte .‫اﻟﺗﺻﻣﯾم‬ ‫ﻋﻣﻠﯾﺔ‬ ‫ﻟﺗﺣﺳﯾن‬ ‫إﻣﻛﺎﻧﯾﺔ‬ ‫أﻛﺑر‬ ‫ﻣﻊ‬ ، BIM ‫اﺗﺟﺎھﺎت‬ ‫ﻗﺎﺋﻣﺔ‬ ‫ﯾﺗﺻدر‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫ﺟﻌل‬ ‫ﻓﻲ‬ ‫ﺗﺳﺎﻋد‬ ‫اﻟﺗﻲ‬ ‫اﻟﺧوارزﻣﯾﺎت‬ ‫واﻟﺳﻼﻟم‬ ‫اﻟﻧواﻓذ‬ ‫وﻣﻌﻠﻣﺎت‬ ، ‫اﻟطواﺑق‬ ‫وارﺗﻔﺎﻋﺎت‬ ، ‫واﻟﻣواد‬ ‫اﻟﺗراﻛﯾب‬ :‫وﻧﺳﺧﮭﺎ‬ ‫اﻟﻌﻧﺎﺻر‬ ‫ﻻﻛﺗﺷﺎف‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫اﺳﺗﺧدام‬ ‫ﯾﻣﻛن‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫ﯾﺣﻠل‬ ، .‫ذﻟك‬ ‫إﻟﻰ‬ ‫وﻣﺎ‬ ، ‫أو‬ ‫ﻟ‬ ‫ﻋ‬ ‫طﺑﻘﺔ‬ ‫ﻋﻠﻰ‬ ‫ًﺎ‬‫ﯾ‬‫ﺗﻠﻘﺎﺋ‬ ‫اﻟﻣﺑﻧﻰ‬ ‫ﻣن‬ ‫اﻟﺷﻣﺎﻟﻲ‬ ‫اﻟﺟﺎﻧب‬ ‫ﻋﻠﻰ‬ ‫اﻟﺟدران‬ ‫ﺗﺣﺻل‬ ‫أن‬ ‫ﯾﻣﻛن‬ ، ‫اﻟﻣﺛﺎل‬ ‫ﺳﺑﯾل‬ ‫ﻋﻠﻰ‬ .‫ﺟدﯾد‬ ‫ﻣﺷروع‬ ‫ﻓﻲ‬ ‫اﻟﻧﻣط‬ ‫ﻧﻔس‬ ‫ﯾطﺑق‬ ‫ﺛم‬ ‫ًﺎ‬‫ﯾ‬‫ﻧﻣوذﺟ‬ ‫ﺎ‬ً‫ﻧﻣوذﺟ‬ ً‫ﺎ‬ https://playground.tensorflow.org/ ‫ﺧوارزﻣﯾﺔ‬ DBSCAN
  • 80. https://bimarabia.com/OmarSelim/ Generative adversarial networks ( ‫اﻟﺗوﻟﯾدﯾﺔ‬ ‫اﻟﺧﺻوﻣﺔ‬ ‫ﺷﺑﻛﺎت‬ ‫اﻟﺗﻲ‬ ‫اﻵﻟﻲ‬ ‫اﻟﺗﻌﻠم‬ ‫ﺷﺑﻛﺎت‬ ‫ﻣن‬ ‫ﻧوع‬ ‫ھﻲ‬ ‫اﻟﺧﺻوﻣﯾﺔ‬ ‫اﻟﺗوﻟﯾدﯾﺔ‬ ‫اﻟﺷﺑﻛﺎت‬ ‫أو‬ GAN ) ‫ﻣﻊ‬ ‫ﻋﺻﺑﯾﺗﯾن‬ ‫ﺷﺑﻛﺗﯾن‬ ‫ﺗﺗﻧﺎﻓس‬ .2014 ‫ﻋﺎم‬ ‫ﻓﻲ‬ ‫وزﻣﻼؤه‬ ‫ﺟودﻓﯾﻠو‬ ‫إﯾﺎن‬ ‫اﺧﺗرﻋﮭﺎ‬ ‫ﻟﻌﺑﺔ‬ ‫ﺷﻛل‬ ‫ﻓﻲ‬ ‫ًﺎ‬‫ﻣ‬‫داﺋ‬ ‫ﻟﯾس‬ ‫وﻟﻛن‬ ‫ًﺎ‬‫ﺑ‬‫ﻏﺎﻟ‬ ، ‫اﻟﻠﻌﺑﺔ‬ ‫ﻧظرﯾﺔ‬ ‫)ﺑﻣﻌﻧﻰ‬ ‫ﻟﻌﺑﺔ‬ ‫ﻓﻲ‬ ‫ﺑﻌﺿﮭﻣﺎ‬ ‫ﻟﻠﺑﯾﺎﻧﺎت‬ ‫ﻣﺷﺎﺑﮭﺔ‬ ‫ﻣﻔﺑرﻛﺔ‬ ‫ﺑﯾﺎﻧﺎت‬ ‫إﻧﺷﺎء‬ ‫ﻋﻠﻰ‬ ‫اﻟﺗدرب‬ ‫ﻣﻧﮭﺎ‬ ‫اﻟﮭدف‬ ( ‫ﺻﻔر‬ ‫ﻣﺣﺻﻠﺗﮭﺎ‬ ‫إﻧﺷﺎء‬ ‫اﻟﺗﻘﻧﯾﺔ‬ ‫ھذه‬ ‫ﺗﺗﻌﻠم‬ .‫ﺑﯾﻧﮭﻣﺎ‬ ‫اﻟﺗﻔرﯾق‬ ‫آﻟﻲ‬ ‫أو‬ ‫ﺑﺷري‬ ‫ﻣراﻗب‬ ‫ﻋﻠﻰ‬ ‫ﯾﺻﻌب‬ ،‫اﻟﺣﻘﯾﻘﯾﺔ‬ ، ‫اﻟﻣﺛﺎل‬ ‫ﺳﺑﯾل‬ ‫ﻋﻠﻰ‬ .‫اﻟﺗدرﯾب‬ ‫ﻟﻣﺟﻣوﻋﺔ‬ ‫اﻹﺣﺻﺎﺋﯾﺔ‬ ‫اﻟﺧﺻﺎﺋص‬ ‫ﺑﻧﻔس‬ ‫ﺟدﯾدة‬ ‫ﺑﯾﺎﻧﺎت‬ ‫ﺣﻘﯾﻘﯾﺔ‬ ‫ﺗﺑدو‬ ‫ﺟدﯾدة‬ ‫ﺻور‬ ‫إﻧﺷﺎء‬ ‫اﻟﻔوﺗوﻏراﻓﯾﺔ‬ ‫اﻟﺻور‬ ‫ﻋﻠﻰ‬ ‫ب‬‫ُدرﱠ‬‫ﻣ‬‫اﻟ‬ GAN ‫ﻟـ‬ ‫ﯾﻣﻛن‬ ‫ﺗم‬ ‫أﻧﮫ‬ ‫ﻣن‬ ‫اﻟرﻏم‬ ‫ﻋﻠﻰ‬ .‫اﻟواﻗﻌﯾﺔ‬ ‫اﻟﺧﺻﺎﺋص‬ ‫ﻣن‬ ‫اﻟﻌدﯾد‬ ‫وﻟﮭﺎ‬ ، ‫اﻟﺑﺷرﯾﯾن‬ ‫ﻟﻠﻣراﻗﺑﯾن‬ ‫ﻟﻠرﻗﺎﺑﺔ‬ ‫اﻟﺧﺎﺿﻊ‬ ‫ﻏﯾر‬ ‫ﻟﻠﺗﻌﻠم‬ ‫اﻟﺗوﻟﯾدي‬ ‫اﻟﻧﻣوذج‬ ‫أﺷﻛﺎل‬ ‫ﻣن‬ ‫ﻛﺷﻛل‬ ‫اﻷﺻل‬ ‫ﻓﻲ‬ ‫اﻗﺗراﺣﮫ‬ ‫اﻟﺗﻌﻠم‬ ، ‫ﻟﻺﺷراف‬ ‫اﻟﺧﺎﺿﻊ‬ ‫ﺷﺑﮫ‬ ‫ﻟﻠﺗﻌﻠم‬ ‫ﻣﻔﯾدة‬ ‫أﻧﮭﺎ‬ ‫ًﺎ‬‫ﺿ‬‫أﯾ‬ GAN ‫ﺷﺑﻛﺎت‬ ‫أﺛﺑﺗت‬ ‫ﻓﻘد‬ ، ‫وﺻف‬ ، 2016 ‫ﻋﺎم‬ ‫ﻧدوة‬ ‫ﻓﻲ‬ . ‫اﻟﻣﻌزز‬ ‫واﻟﺗﻌﻠم‬ ، ‫اﻟﻛﺎﻣل‬ ‫ﻟﻺﺷراف‬ ‫اﻟﺧﺎﺿﻊ‬ ‫ﻣﯾدان‬ ‫ﻓﻲ‬ ‫ﻓﻛرة‬ ‫»أروع‬ ‫ﺑﺄﻧﮭﺎ‬ GAN ‫ﺷﺑﻛﺎت‬ ‫ﻟوﻛون‬ ‫ﯾﺎن‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫ﺧﺑﯾر‬ .«‫اﻟﻣﺎﺿﯾﺔ‬ ‫اﻟﻌﺷرﯾن‬ ‫اﻟﺳﻧوات‬ ‫ﻓﻲ‬ ‫اﻵﻟﻲ‬ ‫اﻟﺗﻌﻠم‬ ، ‫اﻟداﺧﻠﻲ‬ ‫اﻟﺗﺻﻣﯾم‬ ‫ﻟﺗﺻور‬ ‫اﻟواﻗﻌﯾﺔ‬ ‫اﻟﺻور‬ ‫ﺗﻧﺗﺞ‬ ‫اﻟﺗﻲ‬ GANs ‫اﺳﺗﺧدام‬ ‫ﯾﻣﻛن‬ ‫ﻟﻣﺷﺎھد‬ ‫ﻋﻧﺎﺻر‬ ‫أو‬ ‫اﻟﻣﻼﺑس‬ ‫وﻋﻧﺎﺻر‬ ، ‫اﻟﺣﻘﺎﺋب‬ ، ‫واﻷﺣذﯾﺔ‬ ، ‫اﻟﺻﻧﺎﻋﻲ‬ ‫واﻟﺗﺻﻣﯾم‬ Facebook ‫طرف‬ ‫ﻣن‬ ‫اﻟﺷﺑﻛﺎت‬ ‫ﻣن‬ ‫اﻟﻧوع‬ ‫ھذا‬ ‫اﺳﺗﺧدام‬ ‫ﯾﺗم‬ . ‫اﻟﻛﻣﺑﯾوﺗر‬ ‫أﻟﻌﺎب‬ . ‫وأﻧﻣﺎط‬ ، ‫اﻟﺻور‬ ‫ﻣن‬ ‫ﻟﻠﻛﺎﺋﻧﺎت‬ ‫اﻷﺑﻌﺎد‬ ‫ﺛﻼﺛﯾﺔ‬ ‫ﻧﻣﺎذج‬ ‫ﺑﻧﺎء‬ ‫إﻋﺎدة‬ GANs ‫ﻟـ‬ ‫ﯾﻣﻛن‬ .‫اﻟﻔﯾدﯾو‬ ‫ﻓﻲ‬ ‫اﻟﺣرﻛﺔ‬ ‫ﻧﻣﺎذج‬
  • 86. https://bimarabia.com/OmarSelim/ Artificial Intelligence in Practice Concierge robot from IBM Watson Sources: documentarytube, wired, Quora Self-driving cars Google’s AlphaGo Chess Siri(iPhone) Amazon ECHO AI is redefining industries by providing greater personalization to users and automating processes.
  • 87. https://bimarabia.com/OmarSelim/ M L Healthcare Robotics Artificial intelligence and Machine learning are being increasingly used in various functions such as: Image Processing Data Mining Video Games Text Analysis
  • 88. https://bimarabia.com/OmarSelim/ M L Image Processing Optical Character Recognition (OCR) Self-driving cars Image tagging and recognition Sources: Quora, documentarytube, Wikipedia Applications of Machine Learning • ‫ﻋﻠﻰ‬ ‫اﻟﺑرﻧﺎﻣﺞ‬ ‫ﻗدرة‬ ‫ھو‬ ‫اﻟﺻور‬ ‫ﻋﻠﻰ‬ ‫اﻟﺗﻌرف‬ ‫واﻷﺷﺧﺎص‬ ‫واﻷﻣﺎﻛن‬ ‫اﻷﺷﯾﺎء‬ ‫ﻋﻠﻰ‬ ‫اﻟﺗﻌرف‬ ‫اﻟﺻورة‬ ‫ﻓﻲ‬ ‫واﻹﺟراءات‬.
  • 90. https://bimarabia.com/OmarSelim/ • ‫ﻣﺳﺗﺧدﻣﺔ‬ ‫ﺣﯾوﯾﺔ‬ ‫ﻗﯾﺎس‬ ‫ﺗﻘﻧﯾﺔ‬ ‫ھو‬ ‫اﻟوﺟﮫ‬ ‫ﻋﻠﻰ‬ ‫اﻟﺗﻌرف‬ • ‫اﻟﺑﺷرﯾﺔ‬ ‫اﻟوﺟوه‬ ‫ﻋﻠﻰ‬ ‫ﻟﻠﺗﻌرف‬. • ‫ﺗﺟﺎرﯾﺔ‬ ‫وﺗﺳوﯾق‬ ‫ﺗﻌرﯾف‬ ‫ﻛﺄداة‬ ‫ﺷﺎﺋﻊ‬ ‫وھو‬ ‫اﻷﻣﺎن‬ ‫أﻧظﻣﺔ‬ ‫ﻓﻲ‬ ‫اﺳﺗﺧداﻣﮫ‬ ‫ﯾﺗم‬. ‫اﻟوﺟﮫ‬ ‫ﻋﻠﻰ‬ ‫اﻟﺗﻌرف‬ ‫ﻣﺗﻌددة‬ ‫ﺻﻧﺎﻋﺎت‬ ‫ﻓواﺋد‬
  • 91. https://bimarabia.com/OmarSelim/ ‫ﻟﻔﻼﺗر‬ ‫ﯾﻣﻛن‬ Snapchat .‫واﻟطﻌﺎم‬ ‫واﻟرﯾﺎﺿﺔ‬ ‫اﻷﻟﯾﻔﺔ‬ ‫واﻟﺣﯾواﻧﺎت‬ ‫اﻟﻛﺎﺋﻧﺎت‬ ‫ﺻور‬ ‫ﺑﯾن‬ ‫اﻟﺗﻣﯾﯾز‬ ‫اﻟذﻛﯾﺔ‬ ‫ﺗﺣدد‬ .‫اﻟﺻﻠﺔ‬ ‫ذات‬ ‫واﻟﻣﻠﺻﻘﺎت‬ ‫اﻟﺣدود‬ ‫إﻟﻰ‬ ‫ﺗﺷﯾر‬ ‫أن‬ ‫ﯾﻣﻛن‬ Geofilters ‫ﻋواﻣل‬ ‫وﺗﻘﺗرح‬ ‫ﻣوﻗﻌك‬ ‫اﻟﻣوﻗﻊ‬ ‫ﻋﻠﻰ‬ ‫ﺗﻌﺗﻣد‬ ‫ﺗﺻﻔﯾﺔ‬. ‫اﻟﺗﻼﻓﯾﻔﯾﺔ‬ ‫اﻟﻌﺻﺑﯾﺔ‬ ‫اﻟﺷﺑﻛﺎت‬ ‫ﺗﺳﻣﻰ‬ ‫اﻟﺻور‬ ‫ﺗﺻﻧﯾف‬ ‫وﺗﻘﻧﯾﺔ‬ ‫اﻵﻟﻲ‬ ‫اﻟﺗﻌﻠم‬ Snapchat ‫ﻣرﺷﺣﺎت‬ ‫ﺗﺳﺗﺧدم‬ .(CNN) .‫اﻟﻣﺳﺗﺧدﻣﯾن‬ ‫ﻣواﻗﻊ‬ ‫ﻋﻠﻰ‬ ‫ﺗرﻋﺎھﺎ‬ ‫اﻟﺗﻲ‬ ‫اﻟﺗﺟﺎرﯾﺔ‬ ‫اﻟﻌﻼﻣﺎت‬ ‫ﻣن‬ ‫إﯾرادات‬ ‫ًﺎ‬‫ﺿ‬‫أﯾ‬ ‫اﻟﻣرﺷﺣﺎت‬ ‫ھذه‬ ‫ﺗﺣﻘق‬ ‫اﻟﺻور‬ ‫ﻋﻠﻰ‬ ‫اﻟﺗﻌرف‬: Snapchat
  • 92. https://bimarabia.com/OmarSelim/ M L Industrial robotics Human simulation Robotics Humanoid Robot Sources: uiowa.edu, LinkedIn, Hilton Applications of Machine Learning
  • 94. https://bimarabia.com/OmarSelim/ M L Some games implement reinforcement learning Video Games Sources: Quora Applications of Machine Learning
  • 97. https://bimarabia.com/OmarSelim/ ‫ﺣﺎﻟﺔ‬ ‫دراﺳﺔ‬: Your.MD ‫ﻣﺷﻛﻠﺔ‬ • ‫ﺷﺎﺋﻌﺔ‬ ‫ﺷﻛوى‬ ‫ھذه‬ .‫ًﺎ‬‫ﻣ‬‫داﺋ‬ ‫ﻣﺛﻘﻠﯾن‬ ‫اﻷوﻟﯾﺔ‬ ‫اﻟرﻋﺎﯾﺔ‬ ‫وﺟراﺣو‬ ‫اﻟﻌﺎﻣون‬ ‫اﻟﻣﻣﺎرﺳون‬ ‫ﯾﻛون‬ ، ‫اﻟﻣﺗﺣدة‬ ‫اﻟﻣﻣﻠﻛﺔ‬ ‫ﻓﻲ‬ .‫ﻟﻠﻣرﺿﻰ‬ • .‫ًا‬‫د‬‫ﺟ‬ ‫طوﯾﻠﺔ‬ ‫اﻟﻣواﻋﯾد‬ ‫اﻧﺗظﺎر‬ ‫أوﻗﺎت‬
  • 98. https://bimarabia.com/OmarSelim/ M L Healthcare Source: cbinsights Applications of Machine Learning • .‫اﻻﺑﺗداﺋﻲ‬ ‫ﻗﺑل‬ ‫ﻣﺎ‬ ‫ﻟرﻋﺎﯾﺔ‬ ‫ًﺎ‬‫ﻗ‬‫ﺳو‬ Your.MD ‫أﻧﺷﺄت‬ ‫ﻟﻘد‬ • ‫ﺣﯾث‬ ‫ﻋﻣﻠﮭم‬ ‫ﺗﺣﺳﯾن‬ ‫ﻋﻠﻰ‬ ‫وﯾﺳﺎﻋد‬ ‫اﻟطﺑﻲ‬ ‫اﻟطﺎﻗم‬ ‫أﻋﺑﺎء‬ ‫ﻣن‬ ‫ﯾﺧﻔف‬ ‫إﻧﮫ‬ .‫ًﺎ‬‫ﯾ‬‫رﻗﻣ‬ ‫اﻟﺣﺎدة‬ ‫ﻏﯾر‬ ‫ﻟﻠﺣﺎﻻت‬ ‫اﻷوﻟﻲ‬ ‫اﻟﻔﺣص‬ ‫إﺟراء‬ ‫ﯾﻣﻛن‬ • ‫ﻣن‬ ‫ﯾﺗﻠﻘوﻧﮭﺎ‬ ‫اﻟﺗﻲ‬ ‫واﻻﻗﺗراﺣﺎت‬ ‫اﻟﻣﻌﻠوﻣﺎت‬ ‫ﻣن‬ ‫اﻟﺧدﻣﺔ‬ ‫ﻣﺳﺗﺧدﻣو‬ ‫ﯾﺳﺗﻔﯾد‬ .‫اﻟﺗطﺑﯾق‬
  • 99. https://bimarabia.com/OmarSelim/ .‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫ﺑﺎﺳﺗﺧدام‬ ‫اﻟﺳﻛري‬ ‫اﻟﺷﺑﻛﯾﺔ‬ ‫اﻋﺗﻼل‬ ‫أو‬ ‫اﻟﺳﻛري‬ ‫داء‬ ‫ﺗﺷﺧﯾص‬ ‫ﯾﻣﻛن‬ ‫ﻣوﻗﻊ‬ ‫ﻓﻲ‬ ‫ﻧﺷرھﺎ‬ ‫ﯾﺗم‬ ‫واﻟﺗﻲ‬ ، ‫اﻟﻣﺣﻣوﻟﺔ‬ ‫اﻟﻌﯾن‬ ‫ﻗﺎع‬ ‫ﻛﺎﻣﯾرا‬ DR ‫ﻓﺣص‬ ‫ﺑرﻧﺎﻣﺞ‬ ‫ﯾﺳﺗﺧدم‬ .‫اﻟﻔﺣص‬ .‫ﻟﺗﺣﻠﯾﻠﮭﺎ‬ ‫اﻟﺳﺣﺎﺑﯾﺔ‬ ‫اﻟﺑراﻣﺞ‬ ‫ﻣﻧﺻﺔ‬ ‫إﻟﻰ‬ ‫ﺑﺄﻣﺎن‬ ‫اﻟﻣﻠﺗﻘطﺔ‬ ‫اﻟﺻور‬ ‫ﻧﻘل‬ ‫ﯾﺗم‬ .‫ﻟﻠﻣرﯾض‬ ، ‫اﻟﺣﺎﻻت‬ ‫ﺑﻌض‬ ‫وﻓﻲ‬ ، ‫اﻹﺣﺎﻟﺔ‬ ‫ﻣﺻدر‬ ‫ﻟـ‬ ‫ﺗﻘرﯾر‬ ‫ﺑﺈﻧﺷﺎء‬ ‫ًﺎ‬‫ﯾ‬‫ﺗﻠﻘﺎﺋ‬ ‫اﻟﺑرﻧﺎﻣﺞ‬ ‫ﯾﻘوم‬ .‫اﻟﻣﺗﺎﺑﻌﺔ‬ ‫ﻟﻔﺣوﺻﺎت‬ ‫اﻻﻣﺗﺛﺎل‬ ‫ﯾﺳﮭل‬ ‫ھذا‬ ‫ﻓﺣص‬ ‫ﺑرﻧﺎﻣﺞ‬ :‫اﻟﺻﺣﯾﺔ‬ ‫اﻟرﻋﺎﯾﺔ‬ ‫ﻓﻲ‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ DR
  • 100. https://bimarabia.com/OmarSelim/ ‫اﻟﻣﺣﻠول‬ ‫ﺑﮭﺎ‬ ‫اﻟﻣﺳﺗﺧدﻣﯾن‬ ‫ﻟﺗزوﯾد‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫ﺗﻘﻧﯾﺎت‬ ‫ﺗﺳﺗﺧدم‬ ‫ﻣﺟﺎﻧﯾﺔ‬ ‫ﺧدﻣﺔ‬ ‫ھﻲ‬ Your.MD .‫اﻟطﺑﯾﺔ‬ ‫ﺷﻛﺎوﯾﮭم‬ ‫ﺣول‬ ‫ﺷﺧﺻﯾﺔ‬ ‫ﻧﺻﺎﺋﺢ‬ ‫ﻣن‬ ‫ھذا‬ ‫ﺗﺟﻣﯾﻊ‬ ‫ﺗم‬ .‫اﻷﻣراض‬ ‫ﺣول‬ ‫اﻟﺳرﯾرﯾﺔ‬ ‫ﻟﻠﺑﯾﺎﻧﺎت‬ ‫ﺧرﯾطﺔ‬ ‫ﻣﻊ‬ ‫وﯾطﺎﺑﻘﮭﺎ‬ ‫اﻟﻣﺳﺗﺧدﻣﯾن‬ ‫أﻋراض‬ ‫اﻟﺗطﺑﯾق‬ ‫ﯾﺳﺟل‬ .‫اﻟﻣﺳﺎھﻣﯾن‬ ‫اﻷطﺑﺎء‬ ‫ﺑﻣﺳﺎﻋدة‬ ‫ﻋﺎﻣﺔ‬ ‫ﻣﺻﺎدر‬ ‫اﻷﻣراض‬ ‫ﺣول‬ ‫أﺑﺣﺎث‬ ‫ﻹﺟراء‬ ‫ًﺎ‬‫ﺑ‬‫طﺑﯾ‬ 30 ‫ﺣواﻟﻲ‬ Your.MD ‫ﯾﺷرك‬ .‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫ﻧظﺎم‬ ‫ﻓﻲ‬ ‫اﻟﺑﯾﺎﻧﺎت‬ ‫وإدﺧﺎل‬ ‫ﺣﺎﻟﺔ‬ ‫دراﺳﺔ‬: Your.MD
  • 103. https://bimarabia.com/OmarSelim/ ‫ﻣﺛل‬ ‫ﺣﻘﯾﻘﯾﯾن‬ ‫ﻏﯾر‬ ‫ﻷﺷﺧﺎص‬ ‫ﺻور‬ ‫ﺗوﻟﯾد‬ ‫ﯾﻣﻛن‬ GAN ‫ﻋﻠﻰ‬ ‫ﯾﻌﺗﻣد‬ ‫اﻟذي‬ ‫اﻟﻣوﻗﻊ‬ ‫ھذا‬ https://this-person-does-not-exis t.com/en
  • 104. https://bimarabia.com/OmarSelim/ futurepedia ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫اﻟﻣواﻗﻊ‬ ‫ﺑﯾﻧﺎت‬ ‫ﻗﺎﻋدة‬ https://www.futurepedia.io/ https://www.youtube.com/watch?v=v69_gIa8Xts &list=PLNMim060_nUJs5lSTwbFK8Pe1BCUPT_E B&index=177
  • 105. https://bimarabia.com/OmarSelim/ Midjourney Midjourney ‫ﻣوﻗﻊ‬ ‫ﻣن‬ ‫ﻣﻘدﻣﺔ‬ ‫ﻣﺛﻼ‬ ‫اﻟﻣﻘدس‬ ‫ﻛﺗﺎﺑك‬ ‫ﻣن‬ ‫ﻣﺷﺎھد‬ ‫ﺗﺧﯾل‬ ‫او‬ ‫ﻣﻌﻣﺎري‬ ‫ﺗﻛون‬ ‫ﻗد‬ ‫ﺗﺻﺎﻣﯾم‬ ‫و‬ ‫ﻓﻧﯾﺔ‬ ‫اﻋﻣﺎل‬ ‫اﻧﺗﺎج‬ ‫ﻓﻲ‬ ‫اﻟﺻﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫اﺳﺗﺧدام‬ https://www.midjourney.com https://www.midjourney.com/app/ https://discord.com/channels/662267976984297473/997267800106205184 https://www.craiyon.com/ https://stablediffusionweb.com/#demo
  • 106. https://bimarabia.com/OmarSelim/ https://openai.com/dall-e-2/. https://labs.openai.com/ .‫اﻓﺗﺗﺎﺣﯾﺔ‬ ‫ﻛﻠﻣﺎت‬ ‫طﺑﯾﻌﯾﺔ‬ ‫ﺑﻠﻐﺔ‬ ‫وﺻف‬ ‫ﻣن‬ ‫واﻗﻌﯾﺔ‬ ‫وﻓﻧون‬ ‫ﺻور‬ ‫إﻧﺷﺎء‬ ‫ﯾﻣﻛﻧﮫ‬ ‫ﺟدﯾد‬ ‫اﺻطﻧﺎﻋﻲ‬ ‫ذﻛﺎء‬ ‫ﻧظﺎم‬ ‫ھو‬ ‫و‬ DALL · E 2 https://beta.openai.com/examples/ https://pitch.com/v/DALL-E-prompt-book-v1-tmd33y https://looka.com/ Design Logo
  • 107. https://bimarabia.com/OmarSelim/ lexica art ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫ﺑﺎﻟذﻛﺎء‬ ‫اﻟﻣوﻟدﯾﺔ‬ ‫اﻟﺻور‬ ‫ﻋن‬ ‫ﺑﺣث‬ ‫ﻣﺣرك‬ https://lexica.art/
  • 109. https://bimarabia.com/OmarSelim/ text to speech ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫ﺑﺎﻟذﻛﺎء‬ ‫اﻟﻛﻼم‬ ‫إﻟﻰ‬ ‫اﻟﻧص‬ ‫ﺗﺣوﯾل‬ https://www.veed.io/
  • 112. https://bimarabia.com/OmarSelim/ Tarteel: Recite Al Quran https://play.google.com/store/apps/details?id=com.mmmoussa.iqra&hl =ar&gl=US
  • 113. https://bimarabia.com/OmarSelim/ ‫زر‬ ‫ﺑﺿﻐطﺔ‬ ‫ﻣﻘﺎﻟﺗك‬ ‫اﻛﺗب‬ ‫ﻛﺎﺗب‬ https://katteb.com/ar/?track=63d31194e2854
  • 115. https://bimarabia.com/OmarSelim/ generated photos ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫ﺑﺎﻟذﻛﺎء‬ ‫اﺷﺧﺎص‬ ‫وﺟوه‬ ‫ﺗﻛوﯾن‬ https://generated.photos/face-generator
  • 116. https://bimarabia.com/OmarSelim/ RunwayML ‫اﻟﺳﯾﻧﻣﺎﺋﯾﺔ‬ ‫اﻟﺧدع‬ ‫و‬ ‫اﻟﻣﻌزز‬ ‫واﻹﺑداع‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫اﺑﺗﻛﺎرات‬ https://runwayml.com/
  • 117. https://bimarabia.com/OmarSelim/ Image-to-Image Demo Interactive Image Translation with pix2pix-tensorflow Written by Christopher Hesse — February 19th , 2017 Recently, I made a Tensorflow port of pix2pix by Isola et al., covered in the article Image-to-Image Translation in Tensorflow. I've taken a few pre-trained models and made an interactive web thing for trying them out. Chrome is recommended. The pix2pix model works by training on pairs of images such as building facade labels to building facades, and then attempts to generate the corresponding output image from any input image you give it. The idea is straight from the pix2pix paper, which is a good read.
  • 120. https://bimarabia.com/OmarSelim/ synthesia ‫ﺷﮭﯾرة‬ ‫ﻟﺷﺧﺻﯾﺎت‬ ‫ﻣزﯾﻔﺔ‬ ‫ﻓﯾدوھﺎت‬ ‫اﻧﺷﺎء‬ ‫و‬ ‫اﻟﺻﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ https://www.synthesia.io/
  • 121. https://bimarabia.com/OmarSelim/ ‫اﻧﯾﻣﺷن‬ ‫ﻓﯾﻠم‬ ‫ﻟك‬ ‫ﯾﻌﻣل‬ ‫و‬ ‫اﻟﺳﯾﻧﺎرﯾو‬ ‫ﻟك‬ ‫ﯾﻛﺗب‬ ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫ﻣﺟﺎﻧﺎ‬ https://rytr.me/ https://app.steve.ai/
  • 122. https://bimarabia.com/OmarSelim/ ‫اوﻧﻼﯾن‬ ‫اﻟرﺳم‬ ‫و‬ ‫اﻟﺻﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ http://gandissect.res.ibm.com/ganpaint.html?project=churchoutdoor&layer=layer4 http://gandissect.res.ibm.com/ganpaint.html?project=churchoutdoor&layer=layer4 https://storage.googleapis.com/chimera-painter/index.html https://www.autodraw.com/ https://quickdraw.withgoogle.com/#details http://nvidia-research-mingyuliu.com/gaugan
  • 123. https://bimarabia.com/OmarSelim/ nightcafe ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫ﺑﺎﺳﺗﺧدام‬ ‫اﻟﺻور‬ ‫اﻧﺷﺎء‬ https://creator.nightcafe.studio/ https://www.youtube.com/watch?v=92bEJ8l3XEg&list=PLNMim060_nUJs5lSTwbFK8Pe1BCUPT_EB&inde x=87
  • 124. https://bimarabia.com/OmarSelim/ pixray gob io ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫اﻟذﻛﺎء‬ ‫ﺑﺎﺳﺗﺧدام‬ ‫ﺻور‬ ‫ﺗﻛوﯾن‬ https://pixray.gob.io/
  • 125. https://bimarabia.com/OmarSelim/ artbreeder ‫اﻻﺻطﻧﺎﻋﻲ‬ ‫ﺑﺎﻟذﻛﺎء‬ ‫ﺻور‬ ‫ﺗﻛوﯾن‬ https://www.artbreeder.com/