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Machine learning books and papers

Machine learning books and papers

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

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Iran13 749Education8 033

📈 Analytical overview of Telegram channel Machine learning books and papers

Channel Machine learning books and papers (@machine_learn) in the English language segment is an active participant. Currently, the community unites 24 505 subscribers, ranking 8 033 in the Education category and 13 749 in the Iran region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 24 505 subscribers.

According to the latest data from 03 July, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -99 over the last 30 days and by 2 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 6.54%. Within the first 24 hours after publication, content typically collects 2.24% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 1 603 views. Within the first day, a publication typically gains 549 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 1.
  • Thematic interests: Content is focused on key topics such as disorder, psy, مقاله, framework, graph.

📝 Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
“Admin: @Raminmousa ID: @Machine_learn link: https://t.me/Machine_learn”

Thanks to the high frequency of updates (latest data received on 04 July, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Education category.

24 505
Subscribers
+224 hours
-107 days
-9930 days
Posts Archive
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