DATA SCIENCE UCHUN ENG YAXSHI DASTURLASH TILLARI

Authors

  • Saidabonu Shokirova Chirchiq Davlat Pedagogika Universiteti Author

Keywords:

Data Science, dasturlash tillari, Python, R, SQL, Julia, Java, Scala, ma’lumotlar tahlili, mashinaviy o‘rganish, statistik tahlil, Big Data, vizualizatsiya.

Abstract

Ushbu maqola Data Science sohasida eng ko‘p qo‘llaniladigan dasturlash tillarini tahlil qiladi va ularning afzalliklari, kamchiliklari hamda qo‘llanilish sohalari haqida ma’lumot beradi. Python, R, SQL, Julia, Java va Scala tillarining xususiyatlari ko‘rib chiqilib, har bir tilning Data Science loyihalaridagi o‘rni tahlil qilinadi. Maqola yangi boshlovchilar va tajribali mutaxassislar uchun qaysi tilni tanlash bo‘yicha amaliy tavsiyalar beradi. Python’ning ko‘p qirraliligi, R’ning statistik tahlildagi kuchi, SQL’ning ma’lumotlar bazasi bilan ishlashdagi muhimligi, Julia’ning yuqori tezligi, Java va Scala’ning Big Data loyihalaridagi afzalliklari alohida e’tiborga olinadi.

References

1. Matthes, E. (2019). Python Crash Course: A Hands-On, Project-Based Introduction to Programming (2nd ed.). No Starch Press.

2. Guttag, J. V. (2016). Introduction to Computation and Programming Using Python (2nd ed.). MIT Press.

3. D. P. Kroese, T. Taimre, and Z. I. Botev. Handbook of Monte Carlo Methods. John Wiley & Sons, New York, 2011.

4. R. G. Bartle. The Elements of Integration and Lebesgue Measure. John Wiley & Sons, Hoboken, 1995.

5. Raqamli Avlod. (n.d.). Data Science sohasiga qiziqqanlar uchun yo‘l xaritasi. Retrieved from https://raqamliavlod.uz

6. R. Y. Rubinstein. The cross-entropy method for combinatorial and continuous optimization. Methodology and Computing in Applied Probability, 2:127–190, 1999.

7. Mohirdev. (2024). Scala va Spark: Data injenerlar uchun kurslar. Retrieved from https://mohirdev.uz

8. Pyblog. (2022). 2022-yilda mashhur dasturlash tillari: TOP-6 talik. Retrieved from https://pyblog.uz

Downloads

Published

2025-07-30