NEYRON TARMOQLARDA FAOLLASHTIRISH FUNKSIYALARI VA ULARDAN FOYDALANISH
Keywords:
Segregatsiya, kirish qatlami , yashirin qatlam, chiqish qatlami, feedforward propagation , orqaga tarqalish , chiziqli faollashtirish, SigmoidAbstract
Har bir daqiqada miyamiz kiruvchi ma'lumotlarni "foydali" va "foydali bo'lmagan" toifalarga ajratishga harakat qiladi. Bu gap bizning miyamiz uchun ham, mashinani o'rganish uchun ham to'g'ri keladi. Chuqur o'rganishda sun'iy neyron tarmog'i arxitekturalarida shunga o'xshash jarayon sodir bo'ladi. Segregatsiya neyron tarmog'ining to'g'ri ishlashiga yordam berishda muhim rol o'ynaydi va uning foydasiz qismini tahlil qilishda vaqt sarflab qolib ketishdan ko'ra foydali ma'lumotlardan o'rganishini ta'minlaydi. Faollashtirish funksiyasi neyron tarmoqqa muhim maʼlumotlardan foydalanishda yordam beradi va shu bilan birga ahamiyatsiz maʼlumotlar nuqtalarini tashlab ketadi. Neyron tarmoqni qo’llash masalasiga qarab qanday faollashtirish funksiyasi tadbiq etilishi haqida fikr yuritamiz.
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Jo‘rayev S. U. Python programming language and its features //American Journal of Pedagogical and Educational Research Volume 14, | July, 2023
Jo‘rayev S. U. Performing an arithmetic operation in the python programming language //American Journal of Pedagogical and Educational Research Volume 14, | July, 2023
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