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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 24 508 subscribers, ranking 8 014 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 24 508 subscribers.

According to the latest data from 05 July, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -103 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 6.06%. Within the first 24 hours after publication, content typically collects 2.12% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 1 486 views. Within the first day, a publication typically gains 519 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 2.
  • 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 06 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.

24 508
Subscribers
-124 hours
-17 days
-10330 days
Posts Archive
#ResNet #paper @Machine_learn

#GoogleNet #paper @Machine_learn

#AlexNet #paper @Machine_learn

معماری ها و پلتفرم های رایج در حوزه یادگیری عمیق 👇

#Machine_Learning #Cheat_Sheet 💥Machine learning algorithm cheat sheet, Classical Equations, Diagrams and Tricks @Machine_learn

#Machine_Learning #Cheat_Sheet 💥Machine learning algorithm cheat sheet @Machine_learn

#Data_Mining #Recommender_System 🔴Data Mining Methods for Recommender Systems @Machine_learn

#Data_Mining #Recommender_System 🔴The Application of Data-Mining to Recommender Systems @Machine_learn

#Data_Clustering #K_Means 🔴Data clustering: 50 years beyond K-means ➖Pattern Recognition Letters 31 (2010) 651–666 @Machine_learn

#Data_Clustering #Cellular_Automata #Data_Mining 🔴Data clustering using a linear cellular automata-based algorithm ➖Neurocomputing, Volume 114, 19 August 2013, Pages 86–91 @Machine_learn

#Graph_Mining 🔴A SURVEY OF GRAPH MINING TECHNIQUES FOR BIOLOGICAL DATASETS @Machine_learn

#Graph_Mining 🔴Graph Mining: A Survey of Graph Mining Techniques @Machine_learn

#outlier detection for temporal data #paper @Machine_learn

#analysis of different clustering #paper @Machine_learn

@Machine_learn #Book #NLP #Natural_Language_Processing #Text_Mining

#Ensemble Machine Learning - Springer #book @Machine_learn

#deep_learning with tensorflow #book @Machine_learn

#Learning Sentiment-Specific Word Embedding for Twitter Sentiment Classification #paper @Machine_learn

#Word Embedding Revisited: A New Representation Learning and Explicit Matrix #paper @Machine_learn

#Improving Word Embeddings with Convolutional Feature Learning and Subword Information #paper @Machine_learn

Machine learning books and papers - Statistics & analytics of Telegram channel @machine_learn