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Machine Learning

Machine Learning

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Real Machine Learning β€” simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho

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πŸ“ˆ Analytical overview of Telegram channel Machine Learning

Channel Machine Learning (@machinelearning9) in the English language segment is an active participant. Currently, the community unites 40 237 subscribers, ranking 3 336 in the Technologies & Applications category and 227 in the Syria region.

πŸ“Š Audience metrics and dynamics

Since its creation on Π½Π΅Π²Ρ–Π΄ΠΎΠΌΠΎ, the project has demonstrated rapid growth, gathering an audience of 40 237 subscribers.

According to the latest data from 04 July, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 343 over the last 30 days and by 16 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 1.92%. Within the first 24 hours after publication, content typically collects 1.89% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 771 views. Within the first day, a publication typically gains 761 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 3.
  • Thematic interests: Content is focused on key topics such as distance, insidead, gpu, learning, degree.

πŸ“ Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
β€œReal Machine Learning β€” simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho”

Thanks to the high frequency of updates (latest data received on 05 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 Technologies & Applications category.

40 237
Subscribers
+1624 hours
+837 days
+34330 days
Posts Archive
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Join today and get 150% bonus! We will turn Β£100->Β£250 #ad InsideAds
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πŸ“Œ Least Squares Regression, Explained: A Visual Guide with Code Examples for Beginners πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 20
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πŸ“Œ Forecasting the Future: How Can We Predict Tomorrow’s Demand Using Yesterday’s Insights? πŸ—‚ Category: DATA SCIENCE πŸ•’ Date
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πŸ“Œ User Studies for Enterprise Tools: HCI in the Industry πŸ—‚ Category: πŸ•’ Date: 2024-11-06 | ⏱️ Read time: 8 min read Insight
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πŸ“Œ Easy Hurricane Tracking with Tropycal πŸ—‚ Category: DATA VISUALIZATION πŸ•’ Date: 2024-11-06 | ⏱️ Read time: 8 min read A gre
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πŸ“Œ Predict Housing Price using Linear Regression in Python πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-11-06 | ⏱️ Read time: 16 m
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πŸ“Œ Data-Driven Journey Optimization: Using Deep Learning to Design Customer Journeys πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-
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πŸ“Œ Random Forest, Explained: A Visual Guide with Code Examples πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-11-07 | ⏱️ Read time:
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