“DATA SCIENCE JARAYONLARI”

Authors

  • Umarov Bekzod Azizovich Author
  • Nozima Rustamova Shuhratjon qizi Author

Keywords:

Data science, modeling, implementation, statistical analysis, automation, data engineering, visualization, large-scale data collection, diagnostics., Наука о данных, моделирование, внедрение, статистический анализ, автоматизация, инженерия данных, визуализация, крупномасштабный сбор данных, диагностика., Data science , modellashtirish , amaliyotga joriy etish , statistik tahlil, avtomatlashtirish, ma’lumotlar muhandisligi, vizualizatsiya, katta hajmdagi ma’lumotlarni yig’ish, diagnostika.

Abstract

Data science jarayonlari katta hajmdagi ma'lumotlarni yig'ish, tozalash, tahlil qilish, modellashtirish va amaliyotga joriy etish kabi ketma-ket bosqichlarni o'z ichiga oladi. Ushbu jarayonlar yordamida ma'lumotlardan foydali xulosalar chiqarilib, qaror qabul qilish jarayonlari qo'llab-quvvatlanadi. To'g'ri va samarali natijalarga erishish ma'lumotlarning sifati, ishlatiladigan metodlar va texnologiyalar bilan uzviy bog'liq. Data science nafaqat ilmiy izlanishlarda, balki biznes va texnologik yechimlarni ishlab chiqishda ham keng qo'llaniladi.Процессы Data Science включают в себя этапы сбора, очистки, анализа, моделирования и внедрения данных. Эти процессы помогают извлекать полезные выводы из данных и поддерживать процесс принятия решений. Достижение точных и эффективных результатов напрямую связано с качеством данных, используемыми методами и технологиями. Data Science широко применяется не только в научных исследованиях, но и в разработке бизнес- и технологических решений.

Data science processes include stages of data collection, cleaning, analysis, modeling, and implementation. These processes enable the extraction of valuable insights from data and support decision-making processes. Achieving accurate and efficient results is closely tied to data quality, applied methods, and technologies. Data science is widely used not only in scientific research but also in developing business and technological solutions.

Author Biographies

  • Umarov Bekzod Azizovich

    Farg‘ona davlat universiteti amaliy matematika va

     informatika kafedrasi o‘qituvchisi

  • Nozima Rustamova Shuhratjon qizi

    Farg‘ona davlat universiteti talabasi

    nozimaxonrustamova2@gmail.com

References

FOYDALANILGAN ADABIYOTLAR

1."Python for Data Analysis" by Wes McKinney

2."Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow" by Aurélien Géron

3."Data Science from Scratch: First Principles with Python" by Joel Grus

4. "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman

5. "Data Science for Business" by Foster Provost and Tom Fawcett

6. "A Survey on Data Science: Concepts, Techniques, and Applications" (Journal of King Saud University, Computer and Information Sciences)

7. "The Data Science Process: A Survey and Taxonomy" (DOI: 10.1016/j.datak.2019.01.005)

8. Coursera: "Data Science Specialization" by Johns Hopkins University

9. edX: "Data Science for Executives" by Columbia University

10. Udemy: "Complete Data Science Bootcamp"

11."A Survey on Data Science: Concepts, Techniques, and Applications" (Journal of King Saud University, Computer and Information Sciences)

12. "The Data Science Process: A Survey and Taxonomy" (DOI: 10.1016/j.datak.2019.01.005)

13. "Big Data: A Survey" (ACM Computing Surveys)

14."Machine Learning: A Probabilistic Perspective" by Kevin P. Murphy

15. "Understanding Data Science: An Overview of the Field" (Springer)

16. ICML konferensiyasida Data Science va mashina o'qitish sohasidagi ilmiy tadqiqotlar va yondashuvlar taqdim etiladi. Bu yerda maqolada foydalanish uchun dolzarb metodlar va tadqiqotlardan ilhom olish mumkin.

17."Data Science Handbook" by Jake VanderPlas : Bu kitob Data Science jarayonining turli bosqichlarini o'z ichiga oladi, jumladan ma'lumotlarni tahlil qilish, tozalash, mashina o'qitish va natijalarni vizualizatsiya qilish.

18."Deep Learning with Python" by François Chollet : Agar maqolada chuqur o'rganish (deep learning) texnologiyalari va ularning Data Science jarayonidagi roli haqida so'z yuritilsa, bu kitob juda foydali bo'ladi.

Published

2024-12-08

How to Cite

“DATA SCIENCE JARAYONLARI”. (2024). Modern Education and Development, 15(8), 11-16. https://scientific-jl.org/mod/article/view/5112