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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 8 036 in the Education category and 13 785 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 01 July, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -127 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 7.47%. Within the first 24 hours after publication, content typically collects 2.04% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 1 829 views. Within the first day, a publication typically gains 500 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 02 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
-524 hours
-207 days
-12730 days
Posts Archive
100 numpy exercises A joint effort of the numpy community #Numpy #python @Machine_learn

Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review #Paper #ML @Machine_learn

Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review #Paper #ML @Machine_learn

Real-Time Hand sign Recognition using Python and TensorFlow API Check the Article here:- https://codeperfectplus.herokuapp.com/real-time-hand-sign-recogntion-using-tesnorflow Android app download link in the Article. @Machine_learn

A great note to become a data engineer by Chip Huyen: - Data formats - ETL - Batch processing vs Stream processing ... https:
A great note to become a data engineer by Chip Huyen: - Data formats - ETL - Batch processing vs Stream processing ... https://docs.google.com/document/u/0/d/1b9iuZiDEGVLHyMmnf6w2y1aN6yWQhAyqk3GHlpI9q6M/mobilebasic @Machine_learn

سلام از دوستان کسی هست که deep RL optimizationکار کرده باشه؟ جهت انجام یه پروژه ممنون میشم بهم پیام بده: @Raminmousa

Fake News 84 Papers #Fake_News #Papers @Machine_learn

به كانال سيگنال ما بپيونديد: ⚡️⚡️⚡️⚡️⚡️⚡️⚡️⚡️⚡️⚡️ https://t.me/BullsTradingSignal

Machine Learning for Time Series Forecasting with Python (2020) @Machine_learn

سلام و احترام، من روی پایان نامه ارشدم که در حوزه دیپ لرنینگ و تشخیص عنبیه هست دارم کار میکنم در حال حاضر برای جمع آوری دیتا به گوشی سامسونگ اس 10 پلاس یا آیفون 11 نیاز دارم چون کیفیت دوربین بالایی برای عکس گرفتن از عنبیه دارند، از شما دوستان کسی هست که منو کمک کنه، ممنون میشم به آیدی تلگرام من اطلاع بدید. @shohani259

Recent Advances in Language Model Fine-tuning By Sebastian Ruder: https://ruder.io/recent-advances-lm-fine-tuning/ @Machine_learn

The Transformer Network for the Traveling Salesman Problem (video and slides) Another great tutorial from Xavier Bresson on traveling salesman problem (TSP) and recent ML approaches to solve it. It gives a nice overview of the current solvers such as Concorde or Gurobi and their computational complexity. @Machine_learn

سلام دوستان جهت کسب اطلاعات از نحوه خرید می تونین با بنده در ارتباط باشین@Raminmousa
سلام دوستان جهت کسب اطلاعات از نحوه خرید می تونین با بنده در ارتباط باشین@Raminmousa

Filtering DataFrames with the .query() method in Pandas https://jbencook.com/pandas-query/ @Machin_learn
Filtering DataFrames with the .query() method in Pandas https://jbencook.com/pandas-query/ @Machin_learn

Python Data Visualization: Bokeh Cheat Sheet #CheatSheet @Machine_learn