Available now! Telegram Research 2025 โ the year's key insights 
Machine Learning
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Real Machine Learning โ simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho
Show more๐ Analytical overview of Telegram channel Machine Learning
Channel Machine Learning (@machinelearning9) in the English language segment is an active participant. Currently, the community unites 40 114 subscribers, ranking 3 384 in the Technologies & Applications category and 231 in the Syria region.
๐ Audience metrics and dynamics
Since its creation on ะฝะตะฒัะดะพะผะพ, the project has demonstrated rapid growth, gathering an audience of 40 114 subscribers.
According to the latest data from 24 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 401 over the last 30 days and by 38 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 1.96%. Within the first 24 hours after publication, content typically collects 1.16% reactions from the total number of subscribers.
- Post reach: On average, each post receives 788 views. Within the first day, a publication typically gains 465 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 distance, insidead, gpu, learning, degree.
๐ Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
โReal Machine Learning โ simple, practical, and built on experience.
Learn step by step with clear explanations and working code.
Admin: @HusseinSheikho || @Hussein_Sheikhoโ
Thanks to the high frequency of updates (latest data received on 25 June, 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.
40 114
Subscribers
+3824 hours
+637 days
+40130 days
Posts Archive
40 114
๐ Prompt Engineering vs RAG for Editing Resumes
๐ Category: LLM APPLICATIONS
๐ Date: 2026-01-04 | โฑ๏ธ Read time: 12 min read
Running a code-free comparison in Azure
#DataScience #AI #Python
40 114
๐ How to Keep MCPs Useful in Agentic Pipelines
๐ Category: AGENTIC AI
๐ Date: 2026-01-03 | โฑ๏ธ Read time: 10 min read
Check the tools your LLM uses before replacing it with just a more powerful model
#DataScience #AI #Python
40 114
๐ Optimizing Data Transfer in AI/ML Workloads
๐ Category: DEEP LEARNING
๐ Date: 2026-01-03 | โฑ๏ธ Read time: 16 min read
A deep dive on data transfer bottlenecks, their identification, and their resolution with the helpโฆ
#DataScience #AI #Python
40 114
200$ to 20k$ SOL Challenge!
As promised, i will do another challenge for those who missed the previous one!
Last one we completed in 6 days, letโs do this one even quicker!
Join my free group Before closing ๐
https://t.me/+DAKLP7eUy9Y3ZjY0
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40 114
Repost from Machine Learning with Python
All assignments for the #Stanford The Modern Software Developer course are now available online.
This is the first full-fledged university course that covers how code-generative #LLMs are changing every stage of the development lifecycle. The assignments are designed to take you from a beginner to a confident expert in using AI to boost productivity in development.
Enjoy your studies! โ๏ธ
https://github.com/mihail911/modern-software-dev-assignments
https://t.me/CodeProgrammer
40 114
๐ The Real Challenge in Data Storytelling: Getting Buy-In for Simplicity
๐ Category: DATA SCIENCE
๐ Date: 2026-01-02 | โฑ๏ธ Read time: 7 min read
What happens when your clear dashboard meets stakeholders who want everything on one screen
#DataScience #AI #Python
40 114
๐ Off-Beat Careers That Are the Future Of Data
๐ Category: DATA SCIENCE
๐ Date: 2026-01-02 | โฑ๏ธ Read time: 8 min read
The unconventional career paths you need to explore
#DataScience #AI #Python
40 114
๐ Drift Detection in Robust Machine Learning Systems
๐ Category: MACHINE LEARNING
๐ Date: 2026-01-02 | โฑ๏ธ Read time: 18 min read
A prerequisite for long-term success of machine learning systems
#DataScience #AI #Python
40 114
200$ to 20k$ SOL Challenge!
As promised, i will do another challenge for those who missed the previous one!
Last one we completed in 6 days, letโs do this one even quicker!
Join my free group Before closing ๐
https://t.me/+DAKLP7eUy9Y3ZjY0
#ad InsideAds
40 114
๐ Deep Reinforcement Learning: The Actor-Critic Method
๐ Category: REINFORCEMENT LEARNING
๐ Date: 2026-01-01 | โฑ๏ธ Read time: 19 min read
Robot friends collaborate to learn to fly a drone
#DataScience #AI #Python
40 114
Repost from Machine Learning with Python
Harvard has made its textbook on ML systems publicly available. It's extremely practical: not just about how to train models, but how to build production systems around them - what really matters.
The topics there are really top-notch:
> Building autograd, optimizers, attention, and mini-PyTorch from scratch to understand how the framework is structured internally. (This is really awesome)
> Basic things about DL: batches, computational accuracy, model architectures, and training
> Optimizing ML performance, hardware acceleration, benchmarking, and efficiency
So this isn't just an introductory course on ML, but a complete cycle from start to practical application. You can already read the book and view the code for free. For 2025, this is one of the strongest textbooks to have been released, so it's best not to miss out.
The repository is here, with a link to the book inside ๐
๐ @codeprogrammer
40 114
๐ EDA in Public (Part 3): RFM Analysis for Customer Segmentation in Pandas
๐ Category: DATA SCIENCE
๐ Date: 2026-01-01 | โฑ๏ธ Read time: 13 min read
How to build, score, and interpret RFM segments step by step
#DataScience #AI #Python
40 114
๐ The Machine Learning โAdvent Calendarโ Bonus 2: Gradient Descent Variants in Excel
๐ Category: MACHINE LEARNING
๐ Date: 2025-12-31 | โฑ๏ธ Read time: 8 min read
Gradient Descent, Momentum, RMSProp, and Adam all aim for the same minimum. They do notโฆ
#DataScience #AI #Python
40 114
๐ Chunk Size as an Experimental Variable in RAG Systems
๐ Category: LARGE LANGUAGE MODELS
๐ Date: 2025-12-31 | โฑ๏ธ Read time: 12 min read
Understanding retrieval in RAG systems by experimenting with different chunk sizes
#DataScience #AI #Python
40 114
๐ What Advent of Code Has Taught Me About Data Science
๐ Category: PROGRAMMING
๐ Date: 2025-12-31 | โฑ๏ธ Read time: 10 min read
Five key learnings that I discovered during a programming challenge and how they apply toโฆ
#DataScience #AI #Python
40 114
๐ Production-Ready LLMs Made Simple with the NeMo Agent Toolkit
๐ Category: AGENTIC AI
๐ Date: 2025-12-31 | โฑ๏ธ Read time: 23 min read
From simple chat to multi-agent reasoning and real-time REST APIs
#DataScience #AI #Python
40 114
โI spent hours lost in endless Telegram groupsโuntil I discovered this hidden search engine.โ Argo๐Search lets you find the best groups, channels, music, and news in seconds. No more wasting time scrolling!
Discover what others havenโt yet: Try it now and unlock Telegram like never before.
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