Mashinali o’qitishga kirish” fanidan yakuniy nazorat test savollari №1 Fan bobi – 1; Fan bo’limi – 1; Qiyinchilik dara jasi – 1

150 Fan bobi – 7 ; Fan bo’limi – 3; Qiyinchilik darajasi – 1 ;
Gradient tushish-bu?
bu neyron tarmoq parametrlari uchun maqbul qiymatlarni topish uchun iterative ravishda ishlaydigan mashinali o’qitish algoritmi hisoblanadi
bu neyron tarmoq uchun maqbul qiymatlarni topish uchun iterative ravishda ishlaydigan mashinali o’qitish hisoblanadi
bu neyron tarmoq parametrlari uchun maqbul qiymatlarni topish uchun algoritmi hisoblanadi
№151 Fan bobi – 7 ; Fan bo’limi – 3; Qiyinchilik darajasi – 2 ;
Gradient tushish asosida og’irlik koeffitsientlari qaysi qiymatlar asosida ishlatiladi?
learning rate va initial values
Cost funksiyasi
Loss funksiyasi
№152 Fan bobi – 5 ; Fan bo’limi – 3; Qiyinchilik darajasi – 2 ;
DNN-bu?
Chuqur neyron tarmoq
Mashinali o’qitish
Sun’iy neyron tarmoq

№153 Fan bobi – 7 ; Fan bo’limi – 3; Qiyinchilik darajasi – 2 ;

Data label-?
ma’lumotlar nishoni
ma’lumotlar to’plami
muammoni tushuntirish
№154 Fan bobi – 6; Fan bo’limi – 4; Qiyinchilik darajasi – 2 ;
Obtain huge training datasets-?
o’qitish uchun katta ma’lumotlar to’plami
ma’lumotlar nishoni
muammoni tushuntirish
№155 Fan bobi – 7 ; Fan bo’limi – 3; Qiyinchilik darajasi – 2 ;
Explain a problem-?
muammoni tushuntirish
o’qitish uchun katta ma’lumotlar to’plami
ma’lumotlar nishoni muammosi
№156 Fan bobi – 7 ; Fan bo’limi – 3; Qiyinchilik darajasi – 2 ;
Sun’iy intellectni kodsiz yaratish uchun qaysi komandadan foydalaniladi?
Teachable Machine Image Project
Image Model, Standart Model
Image Model
№157 Fan bobi – 6 ; Fan bo’limi – 3; Qiyinchilik darajasi – 2 ;
Sinflashtirish masalasi uchun qaysi funksiyalardan foydalaniladi?
logistic va softmax regressiya
gradient va loss funksiyalari
logistic regressiya
№158 Fan bobi – 7 ; Fan bo’limi – 3; Qiyinchilik darajasi – 2 ;
Sinflashtirishning 2 ta turi qaysilar?
Binomial, Multi-class
Decision tree classification
Sinflashtirish grafigi
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