TURLI TIPDAGI MA’LUMOTLARNI INTELLEKTUAL TAHLIL QILISH VA DATA MINING TEXNOLOGIYALARINING EVOLYUTSIYASI
Keywords:
Kalit so‘zlar: Data Mining, sun’iy intellekt, mashinani o‘qitish, timsollarni aniqlash, belgilar fazosi, Big Data, klasterlash, tasniflash.Abstract
Annotatsiya.
Mazkur maqolada turli tipdagi ma’lumotlarni intellektual tahlil qilish
muammolari hamda Data Mining texnologiyalarining rivojlanish bosqichlari tahlil
qilingan. Predmet soha ob’ektlarini tavsiflashda qo‘llaniladigan belgilar turlari,
ularning turli shkalalarda ifodalanishi va noaniqlik holatlari ko‘rib chiqilgan.
Ma’lumotlarga dastlabki ishlov berish, belgilar fazosini shakllantirish va ob’ektlarni
modellashtirish jarayonlarining intellektual tizimlar yaratishdagi ahamiyati asoslab
berilgan. Shuningdek, Data Mining yo‘nalishining statistik tahlildan boshlab
mashinani o‘qitish, sun’iy intellekt va chuqur o‘rganish texnologiyalarigacha bo‘lgan
evolyutsiyasi yoritilgan. Turli tipli ma’lumotlarni tahlil qilishda tasniflash, klasterlash,
regressiya va bashoratlash usullarining o‘rni ko‘rsatib berilgan. Tadqiqot natijalari
zamonaviy intellektual tizimlarni ishlab chiqishda ma’lumotlarni intellektual tahlil
qilish usullarini takomillashtirish zarurligini ko‘rsatadi.
References
Adabiyotlar
1. Russell S., Norvig P. Artificial Intelligence: A Modern Approach. — 4th ed. —
Pearson, 2021. — 1136 p.
2. Bishop C. M., Bishop H. Deep Learning: Foundations and Concepts. — Springer,
2024.
3. Goodfellow I., Bengio Y., Courville A. Deep Learning. — MIT Press, 2016.
4. Xu D., Tian Y. “A Comprehensive Survey of Clustering Algorithms.” Annals of
Data Science, 2020, Vol. 7, pp. 1–42.
5. Aggarwal C. C. Data Mining: The Textbook. — Springer, 2018. — 734 p.
6. Géron A. Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow.
— 3rd ed. — O’Reilly Media, 2022.
7. Provost F., Fawcett T. Data Science for Business. — 2nd ed. — O’Reilly Media,
2023.
8. Zikopoulos P., deRoos D., Parasuraman K., Deutsch T., Giles J., Corrigan D.
Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming
Data. — McGraw-Hill, 2019.
9. Hashem I.A.T. et al. “The Rise of ‘Big Data’ on Cloud Computing: Review and
Open Research Issues.” Information Systems, 2021.
10. J. McCarthy, M. L. Minsky, N. Rochester, and C. E. Shannon, A Proposal for the
Dartmouth Summer Research Project on Artificial Intelligence, Hanover, NH,
USA: Dartmouth College, 1955.
11. Murphy K. P. Probabilistic Machine Learning: An Introduction. — MIT Press,
2022.
