TENSORFLOW FREYMVORKI: O'RNATISH VA ASOSIY FUNKSIYALAR
Keywords:
TensorFlow, sun’iy intellekt, mashinaviy o‘qitish, chuqur o‘rganish, neyron tarmoqlar, Keras, tensorlar, GPU hisoblash, hisoblash grafigi, model yaratish, modelni o‘qitish, optimizatsiya, yo‘qotish funksiyasi, bashorat qilish, tasvirni tanish, tovushni aniqlash, matnni qayta ishlash, tavsiya tizimlari, TFLite, TensorBoard, data preprocessing, konvolyutsion neyron tarmoqlar (CNN), LSTM, regressiya va klassifikatsiya.Abstract
Ushbu maqolada TensorFlow freymvorkining zamonaviy sun’iy intellekt tizimlaridagi o‘rni, uni kompyuterga o‘rnatish bosqichlari hamda amaliyotda eng ko‘p ishlatiladigan asosiy funksiyalari yoritildi. Maqolada TensorFlow bilan ishlashning oddiy va tushunarli jarayonlari bosqichma-bosqich bayon qilindi. Shuningdek, neyron tarmoqlarni yaratish, modelni o‘qitish va natijalarni baholashda qo‘llaniladigan funksiyalar haqida sodda misollar orqali tushuncha berildi. Material talaba uchun qulay tarzda yozilgan bo‘lib, TensorFlow’dan mustaqil foydalanishni boshlashga yordam beradigan asosiy ma’lumotlarni o‘z ichiga oladi.
References
1. Abadi, M., Agarwal, A., Barham, P. va boshqalar. TensorFlow: Large Scale Machine Learning on Heterogeneous Distributed Systems. arXiv preprint arXiv:1603.04467, 2016.
2. Chollet, F. Deep Learning with Python. Manning Publications, 2017.
3. Géron, A. Hands On Machine Learning with Scikit Learn, Keras, and TensorFlow. 2 edition, O’Reilly Media, 2019.
4. Goodfellow, I., Bengio, Y., & Courville, A. Deep Learning. MIT Press, 2016.
5. Raschka, S. & Mirjalili, V. Python Machine Learning: Machine Learning and Deep Learning with Python, scikit learn, and TensorFlow 2. Packt Publishing, 2019.
6. Vaswani, A., Shazeer, N., Parmar, N. va boshqalar. Attention is All You Need. Adv. in Neural Information Processing Systems, 2017.
7. TensorFlow rasmiy hujjatlari. TensorFlow.org Documentation. Online: https://www.tensorflow.org/ (oxirgi kirish 2025).
8. Keras rasmiy qo‘llanmasi. Keras API Documentation. Online: https://keras.io/ (oxirgi kirish 2025).
9. LeCun, Y., Bengio, Y., & Hinton, G. Deep Learning. Nature, 521, 2015.
10. Brownlee, J. Deep Learning for Time Series Forecasting. Machine Learning Mastery, 2020.
11. Nielsen, M. Neural Networks and Deep Learning. Determination Press, 2015.
12. Alpaydin, E. Introduction to Machine Learning. MIT Press, 2020.
13. Raschka, S. Machine Learning Basics with Python. Packt Publishing, 2018.
14. Jurafsky, D. & Martin, J. H. Speech and Language Processing. Pearson, 2021.
15. Bishop, C. M. Pattern Recognition and Machine Learning. Springer, 2006.
