Machine Learning

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Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho

Network:Machine Learning with Python Syria225 Technologies & Applications3 332...

📈 Analytical overview of Telegram channel Machine Learning

Channel Machine Learning (@machinelearning9) in the English language segment is an active participant. Currently, the community unites 40 323 subscribers, ranking 3 332 in the Technologies & Applications category and 225 in the Syria region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 40 323 subscribers.

According to the latest data from 09 July, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 378 over the last 30 days and by 30 over the last 24 hours, overall reach remains high.

Verification status: Not verified
Engagement rate (ER): The average audience engagement rate is 2.23%. Within the first 24 hours after publication, content typically collects 1.95% reactions from the total number of subscribers.
Post reach: On average, each post receives 897 views. Within the first day, a publication typically gains 788 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 distance, insidead, gpu, learning, degree.

📝 Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
“Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho”

Thanks to the high frequency of updates (latest data received on 10 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.

40 323

Subscribers

+3024 hours

+1067 days

+37830 days

897

Post views

~ 78824 hours

~ 1 02448 hours

2.23%

Engagement rate

~ 2

Posts per day

Ads index

beta

Posts Archive

40 323

📌 Create Your Supply Chain Analytics Portfolio to Land Your Dream Job 🗂 Category: DATA SCIENCE 🕒 Date: 2025-03-31 | ⏱️ Read time: 9 min read A guide for students and professionals to build real-world projects and showcase their skills using…

40 323

📌 A Simple Implementation of the Attention Mechanism from Scratch 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-03-31 | ⏱️ Read time: 10 min read How attention helped models like RNNs mitigate the vanishing gradient problem and capture long-range dependencies…

40 323

📌 Graph Neural Networks Part 3: How GraphSAGE Handles Changing Graph Structure 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-04-01 | ⏱️ Read time: 9 min read And how you can use it for large graphs

40 323

📌 Agentic AI: Single vs Multi-Agent Systems 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-04-01 | ⏱️ Read time: 14 min read Demonstrated by building a tech news agent in LangGraph

40 323

📌 AI in Social Research and Polling 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-04-01 | ⏱️ Read time: 13 min read What do we do when nobody answers the phone?

40 323

📌 The Case for Centralized AI Model Inference Serving 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-04-01 | ⏱️ Read time: 11 min read Optimizing highly parallel AI algorithm execution

40 323

📌 PyScript vs. JavaScript: A Battle of Web Titans 🗂 Category: PROGRAMMING 🕒 Date: 2025-04-02 | ⏱️ Read time: 5 min read Can Python really replace JavaScript for web development?

40 323

📌 The Art of Noise | Diffusion Model 🗂 Category: DEEP LEARNING 🕒 Date: 2025-04-02 | ⏱️ Read time: 36 min read Understanding and implementing a diffusion model from scratch with PyTorch

40 323

📌 Agentic GraphRAG for Commercial Contracts 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-04-02 | ⏱️ Read time: 26 min read Structuring legal information as a knowledge graph to increase the answer accuracy using a LangGraph…

40 323

📌 Kernel Case Study: Flash Attention 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-04-03 | ⏱️ Read time: 16 min read Understanding all versions of flash attention through a triton implementation

40 323

📌 Linear Programming: Managing Multiple Targets with Goal Programming 🗂 Category: DATA SCIENCE 🕒 Date: 2025-04-03 | ⏱️ Read time: 12 min read Part 6: Balancing multiple objectives using the weights and preemptive goal programming approaches

40 323

📌 Are We Watching More Ads Than Content? Analyzing YouTube Sponsor Data 🗂 Category: DATA SCIENCE 🕒 Date: 2025-04-03 | ⏱️ Read time: 21 min read Exploring if sponsor segments are getting longer by the year

40 323

📌 Creating an AI Agent to Write Blog Posts with CrewAI 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-04-04 | ⏱️ Read time: 12 min read How to assemble a crew of AI agents with CrewAI and Python

40 323

📌 On-Premise Computing, Data Career Switches, AI File Readers, and Other March Must-Reads 🗂 Category: THE VARIABLE 🕒 Date: 2025-04-04 | ⏱️ Read time: 3 min read A selection of our most-read and -shared articles of the past month.

40 323

📌 How I Would Learn To Code (If I Could Start Over) 🗂 Category: PROGRAMMING 🕒 Date: 2025-04-04 | ⏱️ Read time: 10 min read How to learn to code in 2025

40 323

📌 Let’s Call a Spade a Spade: RDF and LPG — Cousins Who Should Learn to Live Together 🗂 Category: DATA SCIENCE 🕒 Date: 2025-04-07 | ⏱️ Read time: 20 min read An objective comparison of the RDF and LPG data models

40 323

📌 How to Optimize your Python Program for Slowness 🗂 Category: PROGRAMMING 🕒 Date: 2025-04-07 | ⏱️ Read time: 20 min read Write a short program that finishes after the universe dies

40 323

Nobody told me ETF investing could be this easy—until I saw the real power of sector rotation. I ignored it for years… and lost out on simple, steady income that almost runs on autopilot. You want to see the setup? It’s right here. #إعلان InsideAds

40 323

📌 Avoiding Costly Mistakes with Uncertainty Quantification for Algorithmic Home Valuations 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-04-07 | ⏱️ Read time: 10 min read The simple tricks for using AVMU, or Automated Valuation Model Uncertainty, to make your home…

40 323

📌 Circuit Tracing: A Step Closer to Understanding Large Language Models 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-04-08 | ⏱️ Read time: 7 min read Reverse-engineering large languages models’ computation circuit to understand their decision-making processes