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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 24 509 subscribers, ranking 8 029 in the Education category and 13 742 in the Iran region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 24 509 subscribers.

According to the latest data from 28 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -144 over the last 30 days and by -9 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 6.62%. Within the first 24 hours after publication, content typically collects 1.91% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 1 623 views. Within the first day, a publication typically gains 468 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 29 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.

24 509
Subscribers
-924 hours
-317 days
-14430 days
Posts Archive
Final Edit-Sha.pdf1.28 MB

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جایگاه ۲ و ۳ این مقاله باقی مونده. از دوستان کسی خواست در خدمتم @Raminmousa

با عرض سلام در مقاله ی دوممون ۲ جایگاه برای دوستانی که نیاز دارند در نظر گرفتیم. Title: Beampattern Design in Non-Uniform MIMO Communication ABSTRACT: In recent years and with introduction of 5G cellular network and communication, researchers have shown great interest in Multiple Input Multiple Output (MIMO) communication, an advanced technology. Many studies have examined the problem of designing the beampattern for MIMO communication using uniform arrays and the covariance-based method to concentrate the transmitted power to the users. However, this paper aims to tackle this issue in the context of non-uniform arrays. Previous authors have primarily focused on designing the transmitted beampattern based on the cross-correlation matrix of transmitted signal elements. In contrast, this paper suggests optimizing the positions of transmitted antennas along with the cross-correlation matrix. This approach is expected to produce better results. KEYWORDS: MIMO Communication; Beampattern matching design; Non-uniform arrays Covariance based method. همچنین ژورنال که قرار بفرستیم IEEE Transactions on Aerospace and Electronic Systems: https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=7 می باشد. جهت هماهنگی می تونین با ایدی بنده در ارتباط باشین. @Raminmousa

با عرض سلام در مقاله ی دوممون ۲ جایگاه برای دوستانی که نیاز دارند در نظر گرفتیم. Title: Beampattern Design in Non-Uniform MIMO Communication ABSTRACT: In recent years and with introduction of 5G cellular network and communication, researchers have shown great interest in Multiple Input Multiple Output (MIMO) communication, an advanced technology. Many studies have examined the problem of designing the beampattern for MIMO communication using uniform arrays and the covariance-based method to concentrate the transmitted power to the users. However, this paper aims to tackle this issue in the context of non-uniform arrays. Previous authors have primarily focused on designing the transmitted beampattern based on the cross-correlation matrix of transmitted signal elements. In contrast, this paper suggests optimizing the positions of transmitted antennas along with the cross-correlation matrix. This approach is expected to produce better results. KEYWORDS: MIMO Communication; Beampattern matching design; Non-uniform arrays Covariance based method. همچنین ژورنال که قرار بفرستیم IEEE Transactions on Aerospace and Electronic Systems: https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=7 می باشد. جهت هماهنگی می تونین با ایدی بنده در ارتباط باشین. @Raminmous

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Python.for.Scientists.pdf7.08 MB

با عرض سلام فقط جایگاه ۳ از این مقاله باقی مونده ....

با عرض سلام فقط جایگاه ۲ و ۳ از این مقاله باقی مونده ....

با عرض سلام مقاله Title: Improved Interpretability-Based Training for deep Learning Models in Classification جهت ارسال به https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5962385 با If=10.4 اماده کردیم جایگاه ۲ تا ۵ مقاله خالیه. دوستانی که نیاز دارن میتونن با بنده در ارتباط باشند. @Raminmousa