VEKTORLANGAN HISOBLASH, NORMALLASHTIRISH VA STANDARTLASHTIRISH: ZAMONAVIY MA'LUMOTLARNI QAYTA ISHLASHDA FUNDAMENTAL YONDASHUVLAR.
Keywords:
vektorlangan hisoblash, normallashtirish, standartlashtirish, ma'lumotlarni oldindan qayta ishlash, NumPy, parallel hisoblash, xususiyatlarni shkalalash, mashinali o'qitish, hisoblash samaradorligiAbstract
Ushbu tadqiqot ishida zamonaviy ma'lumotlarni qayta ishlash va mashinali o'qitish algoritmlarida muhim ahamiyat kasb etuvchi vektorlangan hisoblash, normallashtirish va standartlashtirish usullari to'liq tahlil qilingan. Vektorlangan hisoblash katta hajmdagi ma'lumotlar bilan ishlashda hisoblash samaradorligini sezilarli oshiradi va parallel operatsiyalar orqali qayta ishlash vaqtini qisqartiradi. Normallashtirish va standartlashtirish usullari ma'lumotlarni oldindan qayta ishlashda asosiy rol o'ynaydi va modellarning aniqligini hamda barqarorligini ta'minlaydi. Tadqiqotda vektorlangan operatsiyalarning matematik asoslari, ularning dasturlash tillarida amalga oshirilishi va turli algoritmlar bilan integratsiyasi chuqur o'rganilgan. Normallashtirish usullarining turli xillari, ularning qo'llanish sohalari va har birining afzalliklari hamda cheklovi batafsil tahlil qilingan. Standartlashtirish jarayonining statistik asoslari va amaliy tatbiqlari ko'rsatilgan. Olingan natijalar ma'lumotlarni samarali qayta ishlash va yuqori sifatli mashinali o'qitish modellari yaratish uchun amaliy yo'riqnoma vazifasini bajaradi.References
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