Learn Python Coding

Open in Telegram

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 Python India9 923 Technologies & Applications3 407...

📈 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 39 481 subscribers, ranking 3 407 in the Technologies & Applications category and 9 923 in the India region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 39 481 subscribers.

According to the latest data from 05 July, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 345 over the last 30 days and by 10 over the last 24 hours, overall reach remains high.

Verification status: Not verified
Engagement rate (ER): The average audience engagement rate is 1.23%. Within the first 24 hours after publication, content typically collects 1.09% reactions from the total number of subscribers.
Post reach: On average, each post receives 484 views. Within the first day, a publication typically gains 430 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 06 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.

39 481

Subscribers

+1024 hours

+727 days

+34530 days

484

Post views

~ 43024 hours

~ 59848 hours

1.23%

Engagement rate

~ 4

Posts per day

Ads index

beta

Posts Archive

39 480

AI for Games, 3d edition Invite your friends 🌹🌹 @DataScience_Books

39 480

AI for Games, 3d edition 👇👇👇👇👇

39 480

Probabilistic two-stage detection Two-stage object detectors that use class-agnostic one-stage detectors as the proposal network. github: https://github.com/xingyizhou/CenterNet2?utm_source=catalyzex.com paper: https://arxiv.org/pdf/2103.07461.pdf Invite your friends 🌹🌹 @DataScience_Books

39 480

A curated list of awesome Python frameworks, libraries, software and resources. github: https://github.com/vinta/awesome-python Invite your friends 🌹🌹 @DataScience_Books

39 480

Invite your friends 🌹🌹 @DataScience_Books

39 480

Optimal transport in multilayer networks Github: https://github.com/cdebacco/MultiOT Paper: https://arxiv.org/abs/2106.07202v1 Invite your friends 🌹🌹 @DataScience_Books

39 480

Part-aware Panoptic Segmentation Github: https://github.com/pmeletis/panoptic_parts Paper: https://arxiv.org/abs/2106.06351v1 Docs: https://panoptic-parts.readthedocs.io/en/stable Invite your friends 🌹🌹 @DataScience_Books

39 480

Color2Style: Real-Time Exemplar-Based Image Colorization with Self-Reference Learning and Deep Feature Modulation ArXiV: https://arxiv.org/pdf/2106.08017.pdf Invite your friends 🌹🌹 @DataScience_Books

39 480

Python machine learning from scratch Invite your friends 🌹🌹 @DataScience_Books

39 480

Python machine learning from scratch 👇👇👇👇👇

39 480

✅ Graph Transformer Networks: Learning Meta-path Graphs to Improve GNNs Github: https://github.com/seongjunyun/Graph_Transformer_Networks Paper: https://arxiv.org/abs/2106.06218v1 Dataset: https://github.com/Jhy1993/HAN Invite your friends 🌹🌹 @DataScience_Books

39 480

🧩 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

39 480

sticker.webp0.60 KB

39 480

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

39 480

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

39 480

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

39 480

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

39 480

Probabilistic Deep Learning (2020) 👇👇👇👇👇

39 480

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

39 480

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