uz
Feedback
Machine learning books and papers

Machine learning books and papers

Kanalga Telegram’da o‘tish

Admin: @Raminmousa ID: @Machine_learn link: https://t.me/Machine_learn

Ko'proq ko'rsatish
Eron13 749Taʼlim8 033

📈 Telegram kanali Machine learning books and papers analitikasi

Machine learning books and papers (@machine_learn) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 24 505 obunachidan iborat bo'lib, Taʼlim toifasida 8 033-o'rinni va Eron mintaqasida 13 749-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 24 505 obunachiga ega bo‘ldi.

03 Iyul, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni -99 ga, so‘nggi 24 soatda esa 2 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya o‘rtacha 6.54% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 2.24% ini tashkil etuvchi reaksiyalarni to‘playdi.
  • Post qamrovi: Har bir post o‘rtacha 1 603 marta ko‘riladi; birinchi sutkada odatda 549 ta ko‘rish yig‘iladi.
  • Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 1 ta reaksiya keladi.
  • Tematik yo‘nalishlar: Kontent disorder, psy, مقاله, framework, graph kabi asosiy mavzularga jamlangan.

📝 Tavsif va kontent siyosati

Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
“Admin: @Raminmousa ID: @Machine_learn link: https://t.me/Machine_learn”

Yuqori yangilanish chastotasi (oxirgi ma’lumot 04 Iyul, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Taʼlim toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.

24 505
Obunachilar
+224 soatlar
-107 kunlar
-9930 kunlar
Postlar arxiv
Machine learning books and papers
Machine learning books and papers
24 505
Machine Learning for OpenCV A practical introduction to the world of machine learning and image processing using #OpenCV and #Python #book #ML @Machine_learn

Machine learning books and papers
Machine learning books and papers
24 505
Machine Learning for OpenCV A practical introduction to the world of machine learning and image processing using #OpenCV and
Machine Learning for OpenCV A practical introduction to the world of machine learning and image processing using #OpenCV and #Python #book #ML @Machine_learn

Machine learning books and papers
Machine learning books and papers
24 505
Machine Learning Refined Foundations, Algorithms, and Applications JEREMY WATT, REZA BORHANI, AND AGGELOS K. KATSAGGELOS #book #ML @Machine_learn

Machine learning books and papers
Machine learning books and papers
24 505
Machine Learning Refined Foundations, Algorithms, and Applications JEREMY WATT, REZA BORHANI, AND AGGELOS K. KATSAGGELOS #boo
Machine Learning Refined Foundations, Algorithms, and Applications JEREMY WATT, REZA BORHANI, AND AGGELOS K. KATSAGGELOS #book #ML @Machine_learn

Machine learning books and papers
Machine learning books and papers
24 505
@Machine_learn ​​New paper on training with pseudo-labels for semantic segmentation Semi-Supervised Segmentation of Salt Bodi
@Machine_learn ​​New paper on training with pseudo-labels for semantic segmentation Semi-Supervised Segmentation of Salt Bodies in Seismic Images: SOTA (1st place) at TGS Salt Identification Challenge. Github: https://github.com/ybabakhin/kaggle_salt_bes_phalanx ArXiV: https://arxiv.org/abs/1904.04445 #GCPR2019 #Segmentation #CV

Machine learning books and papers
Machine learning books and papers
24 505
Learning Scrapy Learn the art of efficient web scraping and crawling with Python #book #python #Scrapy @Machine_leaen

Machine learning books and papers
Machine learning books and papers
24 505
Learning Scrapy Learn the art of efficient web scraping and crawling with Python #book #python #Scrapy @Machine_leaen
Learning Scrapy Learn the art of efficient web scraping and crawling with Python #book #python #Scrapy @Machine_leaen

Machine learning books and papers
Machine learning books and papers
24 505
ensemble-machine-learning@netWorkArtificial #book @Machine_learn

Machine learning books and papers
Machine learning books and papers
24 505

Machine learning books and papers
Machine learning books and papers
24 505
hands-unsupervised-learning #book @Machine_learn

Machine learning books and papers
Machine learning books and papers
24 505
Machinelearning for text #book @Machine_learn

Machine learning books and papers
Machine learning books and papers
24 505

Machine learning books and papers
Machine learning books and papers
24 505
@Machine_learn #code #paper Y-Autoencoders: disentangling latent representations via sequential-encoding Article: https://arxiv.org/abs/1907.10949 GitHub: https://github.com/mpatacchiola/Y-AE

Machine learning books and papers
Machine learning books and papers
24 505
@Machine_learn #code #paper FixRes is a simple method for fixing the train-test resolution discrepancy. It can improve the performance of any convolutional neural network architecture. Github: https://github.com/facebookresearch/FixRes Article:https://arxiv.org/abs/1906.06423

Machine learning books and papers
Machine learning books and papers
24 505
@Machine_learn #code #paper FixRes is a simple method for fixing the train-test resolution discrepancy. It can improve the pe
@Machine_learn #code #paper FixRes is a simple method for fixing the train-test resolution discrepancy. It can improve the performance of any convolutional neural network architecture. Github: https://github.com/facebookresearch/FixRes Article:https://arxiv.org/abs/1906.06423

Machine learning books and papers
Machine learning books and papers
24 505
Simple Deep Learning for Programmers Write your own modern neural networks in Keras and Python for images and sequence data #By: The Lazy Programmer #book #DL @Machine_learn

Machine learning books and papers
Machine learning books and papers
24 505
Simple Deep Learning for Programmers Write your own modern neural networks in Keras and Python for images and sequence data #
Simple Deep Learning for Programmers Write your own modern neural networks in Keras and Python for images and sequence data #By: The Lazy Programmer #book #DL @Machine_learn

Machine learning books and papers
Machine learning books and papers
24 505
@Machine_learn __________________________ How to Develop an Information Maximizing GAN (InfoGAN) in Keras https://machinelearningmastery.com/how-to-develop-an-information-maximizing-generative-adversarial-network-infogan-in-keras/

Machine learning books and papers
Machine learning books and papers
24 505
Sentiment Analysis by Capsules∗ #paper #DL #SA @Machine_learn

Machine learning books and papers
Machine learning books and papers
24 505
Sentiment Analysis by Capsules∗ #paper #DL #SA @Machine_learn
Sentiment Analysis by Capsules∗ #paper #DL #SA @Machine_learn