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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 8 031 in the Education category and 13 740 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 29 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 -1 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 7.01%. Within the first 24 hours after publication, content typically collects 1.97% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 1 718 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 30 June, 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
-124 hours
-277 days
-13130 days
Posts Archive
book.pdf52.08 MB

Math-for-Programmers.pdf27.72 MB

Python Concurrency with asyncio Matthew Fowler.pdf6.07 MB

با عرض سلام تخفيف ٥٠٪؜ ويژه دو پكيچ كدنويسي و پروژه نويسي تا فردا شب . جهت خريد به ايدي بنده پيام بدين . @Raminmoua

Python Concurrency with asyncio Matthew Fowler.pdf6.07 MB

🔥 Yolo8 is coming! Github Docs Colab @Machine_learn

با عرض سلام از سه مقاله اي كه براي فروش گذاشتيم فقط مقاله ي 3-incaps: inseption capsule with adaptive attention for medical image classification. باقي مونده اگر از دوستان كسي نياز داره مي تونه به بنده پيام بده. @Raminmousa

با عرض سلام براي دوستاني كه نيازمند هستند تخفيف ٧٠٪؜ براي ٢٤ ساعت در نظر گرفتيم براي تهيه مي تونين به بنده پيام بدين @Raminmousa

سلام از این مقالات فقط ۱ و ۳ مونده مورد ۲ رو دوستان برداشتن

با عرض سلام خدمت دوستان عزیز سه عنوان مقاله زیر رو برای فروش گذاشتم 1-Deep learning for crypto illiquidity prediction: hybrid approach 2- IndRNNXGboost: indrnn and XGBoost approach for energy consumption prediction. 3- inseption capsule with adaptive attention for medical image classification. دوستانی که نیاز دارن به بنده پیام بدن. @Raminmousa

•(Multi-Modal Image Fusion) 。(nfrared and visible image fusion) 。 (Medical image fusion) •(Digital Photography Image Fusion) 。(Multi-exposure image fusion) 。(Multi-focus image fusion) • (Remote Sensing Image Fusion) 。(Pansharpening) •(General Image Fusion Framerwork) #(Survey) #(Dataset) #(Evaluation Metric) #(General evaluation metric github.com/miao19980215/Image-Fusion