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Learn Python Coding

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Learn Python through simple, practical examples and real coding ideas. Clear explanations, useful snippets, and hands-on learning for anyone starting or improving their programming skills. Admin: @HusseinSheikho || @Hussein_Sheikho

Network: Machine Learning with PythonIndia9 131Technologies & Applications3 309...

📈 Analytical overview of Telegram channel Learn Python Coding

Channel Learn Python Coding (@pythonre) in the English language segment is an active participant. Currently, the community unites 40 902 subscribers, ranking 3 309 in the Technologies & Applications category and 9 131 in the India region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 40 902 subscribers.

According to the latest data from 12 November, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 88 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 1.87%. Within the first 24 hours after publication, content typically collects 0.89% reactions from the total number of subscribers.
Post reach: On average, each post receives 763 views. Within the first day, a publication typically gains 362 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 math, harvard, oxford, supervision, waybienad.

📝 Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
“Learn Python through simple, practical examples and real coding ideas. Clear explanations, useful snippets, and hands-on learning for anyone starting or improving their programming skills. Admin: @HusseinSheikho || @Hussein_Sheikho”

Thanks to the high frequency of updates (latest data received on 13 November, 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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40 902

Subscribers

+824 hours

+57 days

+8830 days

763

Post views

~ 36224 hours

~ 45648 hours

1.87%

Engagement rate

~ 1

Posts per day

Ads index

Posts Archive

40 901

Advanced Analytics in Power BI with R and Python: Ingesting, Transforming, Visualizing 👇👇👇👇👇

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Learn PHP 8: Using MySQL, JavaScript, CSS3, and HTML5 Invite your friends 🌹🌹 @DataScience_Books

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Python Programming: An Introduction to Computer Science Invite your friends 🌹🌹 @DataScience_Books

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Python Programming: An Introduction to Computer Science Authors: John M. Zelle 👇👇👇👇👇

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♠️ RLCard: A Toolkit for Reinforcement Learning in Card Games Github: https://github.com/datamllab/rlcard DouZero: https://github.com/kwai/DouZero Paper: https://arxiv.org/abs/2106.06135v1 Invite your friends 🌹🌹 @DataScience_Books

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🔍 Advancing computer vision research with new Detectron2 Mask R-CNN baselines Facebook Ai: https://ai.facebook.com/blog/advancing-computer-vision-research-with-new-detectron2-mask-r-cnn-baselines/ Code: https://github.com/facebookresearch/detectron2/blob/master/MODEL_ZOO.md#new-baselines-using-large-scale-jitter-and-longer-training-schedule Tensorflow implementation: https://github.com/tensorflow/tpu/tree/master/models/official/detectiona Invite your friends 🌹🌹 @DataScience_Books

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Data Mining. Practical Machine Learning Tools and Techniques, Fourth Edition Invite your friends 🌹🌹 @DataScience_Books

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Data Mining. Practical Machine Learning Tools and Techniques, Fourth Edition 👇👇👇👇👇

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Title: Best way to convert #Python file to #Exe. Invite your friends 👇 @CodeProgrammer

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Hands-On GPU-Accelerated Computer Vision with OpenCV and CUDA: Effective Techniques for Processing Complex Image Data in Real Time Using GPUs Invite your friends 🌹🌹 @DataScience_Books

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Hands-On GPU-Accelerated Computer Vision with OpenCV and CUDA: Effective Techniques for Processing Complex Image Data in Real Time Using GPUs 👇👇👇👇👇

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XCiT: Cross-Covariance Image Transformers Github: https://github.com/facebookresearch/xcit Paper: https://arxiv.org/abs/2106.09681v1 Invite your friends 🌹🌹 @DataScience_Books

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SimSwap: An Efficient Framework For High Fidelity Face Swapping! 😯 👉🏼 GitHub repo: https://github.com/neuralchen/SimSwap 👉🏼 Paper: https://arxiv.org/pdf/2106.06340v1.pdf Invite your friends 🌹🌹 @DataScience_Books

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Beginning Machine Learning in the Browser (2021) Invite your friends 🌹🌹 @DataScience_Books

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