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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
1512.03385.pdf8.00 KB

فقط تا #امشب شب فرصت تهيه پكيچ باقي مانده دوستاني كه نياز دارن به ايدي بنده مراجعه كنن. @Raminmousa

Periodicity in Cryptocurrency Volatility and Liquidity #Paper @Machine_learn

Cryptocurrency liquidity and volatility interrelationships during the COVID-19 pandemic #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 ‏❯ تنسورفلو 1⃣ @cvision ‏❯ آموزش پایتون : 1️⃣ @pythony 2️⃣ @raspberry_python 3️⃣ @pythonchallenge

فقط تا فردا شب فرصت تهيه پكيچ باقي مانده دوستاني كه نياز دارن به ايدي بنده مراجعه كنن. @Raminmousa

Abstract: SuperpixelGridMasks. It is a data augmentation approach which permits to generate various complementary images from original sensor-based data of varied natures e.g. X-Ray scans, vehicular scenes, people images (see data samples). This approach allows to increase the size of your image-based training datasets towards expecting better performances in your analysis tasks. Experiments have shown that the approach can be efficient for image classification tasks. Link: https://www.researchgate.net/publication/360062941_SuperpixelGridCut_SuperpixelGridMean_and_SuperpixelGridMix_Data_Augmentation @Machine_learn

فقط تا چند روز تا پایان تخفیف ویژه @Raminmousa

When the code works anyway ♥️😂 @Machine_learn
When the code works anyway ♥️😂 @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 ‏❯ یادگیری ماشین و یادگیری عمیق : 1️⃣ @Machine_learn 2⃣ @Programming4all_0to100 ‏❯ آموزش پایتون : 1️⃣ @pythony 2️⃣ @raspberry_python 3️⃣ @pythonchallenge

با عرض سلام تمامی مبلغ پیکج های تدریس بنده برای نیازمندان در نظر گرفته شده است. دوستانی که نیاز دارند می توانند به ایده ی بنده مراجعه کنند. این تخفیف تنها برای ماه #رمضان می باشد @Raminmousa

A Survey on EEG Signal Processing Techniques and Machine Learning: Applications to the Neurofeedback of Autobiographical Memory Deficits in Schizophrenia #EEG #ML #DL @Machine_learn

Deep Learning for EEG Data Analytics: A Survey #EEG #Deeplearing #Paper @Machine_learn