MULTITIPLI MA’LUMOTLARGA INTELLEKTUAL ISHLOV BERISH
Keywords:
Multitipli ma’lumotlar, Discrete Fourier Transform, Principal Component Analysis, K-Means Clustering, Tokenizatsiya, Stem-ming, Lemmatization, Word2Vec, TF-IDF, NLTK, spaCyAbstract
Bigdatalarning paydo bo'lishi raqamli, toifali, matnli va tasvirli kabi turli xil ma'lumotlar turlarini o'z ichiga olgan davrni boshladi. Bunday multitipli ma'lumotlardan samarali foydalanish turli sohalarda, jumladan, mashinani o'rganish, data science va sun'iy intellektda hal qiluvchi vazifaga aylandi. Ushbu maqola multitipli ma'lumotlarni qayta ishlashni o'rganish, tahlil qilish va qaror qabul qilishni yaxshilash uchun ma'lumotlar manbalarini integratsiyalash usullarini, qiyinchiliklarini va imkoniyatlarini muhokama qilishdan iborat.
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