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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 24 502 subscribers, ranking 8 053 in the Education category and 13 774 in the Iran region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 24 502 subscribers.

According to the latest data from 30 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -131 over the last 30 days and by -4 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 7.24%. Within the first 24 hours after publication, content typically collects 1.98% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 1 773 views. Within the first day, a publication typically gains 484 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 01 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.

24 502
Subscribers
-424 hours
-187 days
-13130 days
Posts Archive
B978-0-12-810408-8.00019-5.pdf1.82 MB

B978-0-12-810408-8.00013-4.pdf1.25 MB

🔸لیستی از برترین کانال‌های آموزشی در زمینه های هوش‌مصنوعی, پایتون و یادگیری ماشین ‏❯ هوش مصنوعی: 1️⃣ @Ai_Tv 2️⃣ @ai_python 3️⃣ @HomeAI 4⃣ @eventai ‏❯ یادگیری ماشین و یادگیری عمیق : 1️⃣ @Machine_learn 2⃣ @Programming4all_0to100 ‏❯ منابع یادگیری برنامه‌نویسی : 1️⃣ @pythony ‏❯ آموزش پایتون: ‏ 1⃣ @raspberry_python 2⃣ @pythonchallenge 3⃣ @SQL_Server

با عرض سلام بسياري از دوستان راجع به اين پكيج سوال پرسيدن #تخفيفات متاسفانه فقط براي رمضان بود. با تشكر

#Chapter 3, 10, 12 ? @Raminmousa

Chest Radiograph Pathology Categorization via Transfer Learning #Chapter13 @Machine_learn

Scalable High Performance Image Registration Framework by Unsupervised Deep Feature Representations Learning #Chapter11 @Machine_learn

Deformable MR Prostate Segmentation via Deep Feature Learning and Sparse Patch Matching #Chapter9 @Machine_learn

Deep Learning Tissue Segmentation in Cardiac Histopathology Images #Chapter8 @Machine_learn

Deep Voting and Structured Regression for Microscopy Image Analysis #Chapter7 @Machine_learn

Deep Cascaded Networks for Sparsely Distributed Object Detection from Medical Images #Chapter6 @Machine_learn

Automatic Interpretation of Carotid Intima–Media Thickness Videos Using Convolutional Neural Networks #Chapter5 @Machine_learn

Multi-Instance Multi-Stage Deep Learning for Medical Image Recognition #Chapter4 @Machine_learn

An Introduction to Deep Convolutional Neural Nets for Computer Vision #Chapter2 @Machine_learn

An Introduction to Neural Networks and Deep Learning #Chapter1 @Machine_learn

Predicting academic performance by considering student heterogeneity #Paper @Machine_learn

🔸لیستی از برترین کانال‌های آموزشی در زمینه های هوش‌مصنوعی, پایتون و یادگیری ماشین ‏❯ هوش مصنوعی: 1️⃣ @Ai_Tv 2️⃣ @ai_python 3️⃣ @HomeAI 4⃣ @eventai ‏❯ یادگیری ماشین و یادگیری عمیق : 1️⃣ @Machine_learn 2⃣ @Programming4all_0to100❯ علم داده : 1⃣ @mr_ie ‏❯ آموزش پایتون : 1️⃣ @pythony 2️⃣ @raspberry_python 3️⃣ @pythonchallenge 4⃣ @Koolac_Org

اگر میخواهید در سریع ترین زمان ممکن اپلیکیشن های هوش مصنوعی را توسعه کنید پس همین الان به جمع انجمن برنامه نویسان جولیا بپیوندید . @julia_programming @julia_programming @julia_programming