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Machine learning books and papers

Machine learning books and papers

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📈 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 24 500 subscribers, ranking 8 030 in the Education category and 13 729 in the Iran region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 24 500 subscribers.

According to the latest data from 08 July, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -104 over the last 30 days and by 5 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 6.13%. Within the first 24 hours after publication, content typically collects 2.02% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 1 502 views. Within the first day, a publication typically gains 495 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 2.
  • 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 09 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.

24 500
Subscribers
+524 hours
+67 days
-10430 days
Posts Archive
DeepNeuralNetwork.py0.10 KB

استفاده ReLU در شبکه cnn (ALexNET)

مقاله آقای Hinton در رابطه با ReLU

DeepConvNet MNIST.zip0.23 KB

mnist.pkl.gz15.42 MB

اسلاید جلسه دوم کارگاه یادگیری عمیق-قسمت دوم

اسلاید جلسه دوم کارگاه یادگیری عمیق-قسمت اول

اسلایدهای جلسه اول کارگاه یادگیری عمیق

ImageNet Classification with Deep Convolutional Neural Networks ALEXNET 2012 @deeplearningiran

Neural Episodic Control.pdf2.42 MB

4_5951597037458817346.pdf1.35 MB

طبقه بندی مجموعه داده ImageNet با شبکه های عصبی ژرف کانولوشن #ImageNet_Classification_With_CNN @deeplearningiran
طبقه بندی مجموعه داده ImageNet با شبکه های عصبی ژرف کانولوشن #ImageNet_Classification_With_CNN @deeplearningiran

اصول یادگیری عمیق @deeplearningiran

معماری های یادگیری ژرف در هوش مصنوعی @deeplearningiran

کتاب خوب برای شروع شبکه های عصبی در TensorFlow @deeplearningiran

طبقه بندی مجموعه داده ImageNet با شبکه های عصبی ژرف کانولوشن @deeplearningiran http://yann.lecun.com/exdb/lenet/index.html

Применение генетических алгоритмов совместо с обучением с подкрепления для поиска оптимальных стратегий. Интересно, что статья анонимная и подвергающаяся двойной слепой рецензии. https://openreview.net/pdf?id=ByOnmlWC-

Deep Learning and Data Labeling for Medical Applications.pdf46.02 MB

ml_genetic2.ppt2.07 KB

ml_genetic1.ppt9.43 KB