Mashinali o’qitishga kirish” fanidan mustaqil ish №2

MUXAMMAD AL-XORAZMIY NOMIDAGI
TOSHKENT AXBOROT TEXNOLOGIYALARI UNIVERSITETI
SAMARQAND FILIALI

KOMPYUTER TIZIMLARI KAFEDRASI

5330500- Kompyuter injiniring (Kompyuter injiniring) ta'lim yo'nalishi

“Mashinali o’qitishga kirish” fanidan

MUSTAQIL ISH № 2

Mavzu: Stoxastik gradiyent tushish.

Bajardi: ____________ 3-kurs talabasi Safarov S.

Qabul qildi: ___________ Kubayev S.T.

Ishni bahosi: ___________ ball

Samarqand – 2022

Mavzu rejasi:

1. Gradient tushishi - Gradient descent.

2. Gradient tushishini tushunish uchun o'xshashlik.

3. Asosiy xulosalar.

Tayanch iboralar: GNU (oktavani sozlash), Eyforiya (Euphoria),kompyuterli modellar (computer models), neyronli to’rlar (neural networks), evolyutsiyali hisoblash (evolutionary computation), noravshan mantiq (fuzzy logic),gibridli boshqarish tizimlari, (Hybrid Control Systems), tasvirlarni ishlash (image processing), mashinali ko’rish (computer vision), anglash (recognition), sinflash (classification), ekspert tizim (expert system), tahlil (analysis), bilimlarni modellashtirish (knowledge modeling), dinamikli rejalashtirish tizimi (dynamic scheduling system), sun’iy ilovalar (intelligent applications), taqsimotli hisoblashlar (distributed computing), operatsion tizimlar (OS), sun’iy injeneriya (intelligent engineering), o’zini-o’zi tashkil qiluvchi SUBD (self-organized database), avtomatik tahlil (automatic analysis), OLAP, tibbiy tizimlar (Medical Systems), E-marketlar (E-markets), E-auksionlar (E-auctions),bio-informatika (bio-informatics), DNK-hisoblovchilar (DNA calculators), DARPA, avtomatik anglash (automatic recognition), tasvilarni anglash ( image recognition), nutqni anglash (speech recognition), signallarni anglash (signal recognition), sun’iy interfeysli modellar (Mining Model interface), moliyalashtirishni bashoratlash (financial forecasting), ma’lumotlarni topish (data excavation), tizimlarni tashxislash (Diagnosis systems), ma’lumotlarni shifrlash (data encryption).