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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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Machine Learning with PythonNetwork:Machine Learning with PythonSyria211Technologies & Applications3 201

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 41 884 subscribers, ranking 3 201 in the Technologies & Applications category and 211 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 41 884 subscribers.

According to the latest data from 25 October, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 466 over the last 30 days and by 7 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 5.36%. Within the first 24 hours after publication, content typically collects 1.97% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 2 244 views. Within the first day, a publication typically gains 824 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 5.
  • 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 26 October, 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.

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41 884
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Machine Learningverified-telegram-icon
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πŸ”– 637 interactive modules on ML and AI On VizLearn, you can visually explore: 🫑 Gradient descent; 🫑 SVM and PCA; 🫑 Bayes'
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Agentic AI is the future. If you want to become god-level with AI agents, save these 10 GitHub repos: 1 Awesome LLM Apps πŸ”— https://github.com/Shubhamsaboo/awesome-llm-apps 2 Generative AI for Beginners πŸ”— https://github.com/microsoft/generative-ai-for-beginners 3 LLM Course πŸ”— https://github.com/mlabonne/llm-course 4 Prompt Engineering Guide πŸ”— https://github.com/dair-ai/Prompt-Engineering-Guide 5 AI Agents for Beginners πŸ”— https://github.com/microsoft/ai-agents-for-beginners 6 AI Agents Projects πŸ”— https://github.com/ashishpatel26/500-AI-Agents-Projects 7 Hugging Face Agents Course πŸ”— https://github.com/huggingface/agents-course 8 Awesome AI Agents πŸ”— https://github.com/e2b-dev/awesome-ai-agents 9 GenAI Agents πŸ”— https://github.com/NirDiamant/GenAI_Agents 10 Agents Towards Production πŸ”— https://github.com/NirDiamant/agents-towards-production Anything else you'd add?
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