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Machine Learning with Python

Machine Learning with Python

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Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho

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πŸ“ˆ Analytical overview of Telegram channel Machine Learning with Python

Channel Machine Learning with Python (@codeprogrammer) in the English language segment is an active participant. Currently, the community unites 67 902 subscribers, ranking 2 401 in the Education category and 4 810 in the India 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 67 902 subscribers.

According to the latest data from 13 July, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 89 over the last 30 days and by -8 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 1.73%. Within the first 24 hours after publication, content typically collects 1.57% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 1 175 views. Within the first day, a publication typically gains 1 063 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 insidead, learning, degree, evaluation, algorithm.

πŸ“ Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
β€œLearn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho”

Thanks to the high frequency of updates (latest data received on 14 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.

67 902
Subscribers
-824 hours
+817 days
+8930 days
Posts Archive
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Repost from Machine Learning
Diving deep into Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP. πŸ€–πŸ§  Lectures: πŸŽ“πŸ“š https
Diving deep into Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP. πŸ€–πŸ§  Lectures: πŸŽ“πŸ“š https://github.com/kmario23/deep-learning-drizzle #DeepLearning #MachineLearning #AI #ReinforcementLearning #ComputerVision #NLP ✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk ⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A

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Reinforcement Learning Methods and Tutorials In these tutorials for reinforcement learning, it covers from the basic RL algor
Reinforcement Learning Methods and Tutorials In these tutorials for reinforcement learning, it covers from the basic RL algorithms to advanced algorithms developed recent years. Learning Resources: https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow Here's a collection of simple materials on methods and practical guides, covering both basic reinforcement learning algorithms and modern, recently developed, and updated advanced algorithms.

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Repost from Data Analytics
πŸ”– One of the most useful books on Agentic AI This is not just a textbook, but a comprehensive overview of modern LLMs, model
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