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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 40 895 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 40 895 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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40 895

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

40 895

🧩 A Bayesian Analysis of Lego Prices in Python with PyMC3 https://austinrochford.com/posts/2021-06-10-lego-pymc3.html Lego Price Analysis: https://austinrochford.com/posts/2021-06-03-vader-meditation.html Invite your friends 🌹🌹 @DataScience_Books

40 895

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40 895

A Deep Variational Approach to Clustering Survival Data Github: https://github.com/i6092467/vadesc Paper: https://arxiv.org/abs/2106.05763v1 Invite your friends 🌹🌹 @DataScience_Books

40 895

Pivotal Tuning for Latent-based Editing of Real Images Github: https://github.com/Talegqz/unsupervised_co_part_segmentation Paper: https://arxiv.org/abs/2106.05897v1 Invite your friends 🌹🌹 @DataScience_Books

40 895

Microsoft's FLAML - Fast and Lightweight AutoML Github: https://github.com/microsoft/FLAML Code: https://github.com/microsoft/FLAML/tree/main/notebook/ Paper: https://arxiv.org/abs/2106.04815v1 Invite your friends 🌹🌹 @DataScience_Books

40 895

Probabilistic Deep Learning (2020) Invite your friends 🌹🌹 @DataScience_Books

40 895

Probabilistic Deep Learning (2020) 👇👇👇👇👇

40 895

GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings Github: https://github.com/rusty1s/pyg_autoscale Paper: https://arxiv.org/abs/2106.05609v1 Invite your friends 🌹🌹 @DataScience_Books

40 895

Internet of Things Programming Projects Invite your friends 🌹🌹 @DataScience_Books

40 895

Internet of Things Programming Projects 👇👇👇👇👇

40 895

Principles Of Internet Of Things (IoT) Ecosystem: Insight Paradigm Invite your friends 🌹🌹 @DataScience_Books

40 895

Principles Of Internet Of Things (IoT) Ecosystem: Insight Paradigm 👇👇👇👇👇

40 895

Score Matching Model for Unbounded Data Score Github: https://github.com/Kim-Dongjun/UNCSN Paper: https://arxiv.org/abs/2106.05527v1 Invite your friends 🌹🌹 @DataScience_Books

40 895

👨 TFace: A trusty face recognition research platform Github: https://github.com/Tencent/TFace Paper: https://arxiv.org/abs/2106.05519v1 Invite your friends 🌹🌹 @DataScience_Books

40 895

Representation Learning for Natural Language Processing (2020) Invite your friends 🌹🌹 @DataScience_Books

40 895

Representation Learning for Natural Language Processing (2020) 👇👇👇👇👇

40 895

Pretraining Representations for Data-Efficient Reinforcement Learning Github: https://github.com/mila-iqia/spr Paper: https://arxiv.org/abs/2106.04799v1 Invite your friends 🌹🌹 @DataScience_Books

40 895

Learn R-As a Language Invite your friends 🌹🌹 @DataScience_Books

40 895

Learn R-As a Language Authors: Pedro J. Aphalo (Author) Year: 2020 Edition: 1 👇👇👇👇👇

40 895

Technologies and Applications: Proceedings of AMLTA 2021 Invite your friends 🌹🌹 @DataScience_Books