Abstract
Belgilarni tasniflash zamonaviy texnologiyalar va ilmiy izlanishlar fonida juda katta ahamiyat kasb etayotgan sohalardan biridir. Ushbu jarayonning maqsadi, turli manbalardan olingan ma’lumotlarni aniqlash, ularni ma’lum turkumlarga ajratish va keyinchalik turli sohalarda foydalanishdir. Belgilarni tasniflash asosan matn, tasvir va boshqa raqamli muhitlarda qo‘llaniladi va bu, o‘z navbatida, ko‘plab amaliyot va tadqiqotlar uchun asos bo‘ladi.
References
Brown, T. B., Mann, B., Ryder, N., et al. (2020). "Language Models are Few-Shot Learners." arXiv preprint arXiv:2005.14165.
Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2019). "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding." arXiv preprint arXiv:1810.04805.
He, K., Zhang, X., Ren, S., & Sun, J. (2016). "Deep Residual Learning for Image Recognition." IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
Шердoр А., Шукруллoев Б. Mнoгoфактoрный экoнomетрический анализ в рынoчнoй экoнomикеmнoгoфактoрный экoнomетрический анализ в рынoчнoй экoнomике //Science and Society. – 2024. – Т. 1. – №. 7. – С. 19-26.
Bektosh Sh., Misliddin M. Using Python in the analysis of econometric models //Innovations in exact science. – 2024. – Т. 1. – №. 2. – С. 19-27.