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Machine Learning

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

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📈 Analytical overview of Telegram channel Machine Learning

Channel Machine Learning (@machinelearning9) in the English language segment is an active participant. Currently, the community unites 40 365 subscribers, ranking 3 329 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 40 365 subscribers.

According to the latest data from 11 July, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 393 over the last 30 days and by 17 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 2.29%. Within the first 24 hours after publication, content typically collects 1.74% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 924 views. Within the first day, a publication typically gains 702 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 4.
  • 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 12 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.

40 365
Subscribers
+1724 hours
+1237 days
+39330 days
Posts Archive
📌 How Not to Mislead with Your Data-Driven Story 🗂 Category: DATA SCIENCE 🕒 Date: 2025-07-23 | ⏱️ Read time: 22 min read D
📌 How Not to Mislead with Your Data-Driven Story 🗂 Category: DATA SCIENCE 🕒 Date: 2025-07-23 | ⏱️ Read time: 22 min read Data storytelling can enlighten—but it can also deceive. When persuasive narratives meet biased framing, cherry-picked…

📌 Multi-head Attention is a Fancy Addition Machine 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-07-24 | ⏱️ Read time: 8 min r
📌 Multi-head Attention is a Fancy Addition Machine 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-07-24 | ⏱️ Read time: 8 min read “Attention is All you Need” showed attention as a sequence of multiplicative and concat operations…

📌 Why BI in the AI Age 🗂 Category: SPONSORED CONTENT 🕒 Date: 2025-07-24 | ⏱️ Read time: 9 min read An argument for human-l
📌 Why BI in the AI Age 🗂 Category: SPONSORED CONTENT 🕒 Date: 2025-07-24 | ⏱️ Read time: 9 min read An argument for human-led analysis (at least for now)

📌 Preventing Context Overload: Controlled Neo4j MCP Cypher Responses for LLMs 🗂 Category: AGENTIC AI 🕒 Date: 2025-09-07 |
📌 Preventing Context Overload: Controlled Neo4j MCP Cypher Responses for LLMs 🗂 Category: AGENTIC AI 🕒 Date: 2025-09-07 | ⏱️ Read time: 4 min read How timeouts, truncation, and result sanitization keep Cypher outputs LLM-ready

📌 The Beauty of Space-Filling Curves: Understanding the Hilbert Curve 🗂 Category: MATH 🕒 Date: 2025-09-07 | ⏱️ Read time:
📌 The Beauty of Space-Filling Curves: Understanding the Hilbert Curve 🗂 Category: MATH 🕒 Date: 2025-09-07 | ⏱️ Read time: 17 min read A quick journey from theory to implementation and application

📌 LLMs Continue to Evolve. So Should Your Skill Set. 🗂 Category: THE VARIABLE 🕒 Date: 2025-07-24 | ⏱️ Read time: 3 min rea
📌 LLMs Continue to Evolve. So Should Your Skill Set. 🗂 Category: THE VARIABLE 🕒 Date: 2025-07-24 | ⏱️ Read time: 3 min read This week, we highlight three articles that focus on emerging topics and techniques around large…

📌 Automating Ticket Creation in Jira With the OpenAI Agents SDK: A Step-by-Step Guide 🗂 Category: ARTIFICIAL INTELLIGENCE �
📌 Automating Ticket Creation in Jira With the OpenAI Agents SDK: A Step-by-Step Guide 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-07-24 | ⏱️ Read time: 16 min read Learn how to create AI Agents using the OpenAI Agents SDK to automate Jira ticket…

📌 Optimize for Impact: How to Stay Ahead of Gen AI and Thrive as a Data Scientist 🗂 Category: DATA SCIENCE 🕒 Date: 2025-07
📌 Optimize for Impact: How to Stay Ahead of Gen AI and Thrive as a Data Scientist 🗂 Category: DATA SCIENCE 🕒 Date: 2025-07-24 | ⏱️ Read time: 13 min read The data scientists who survive won’t be the ones who code better than ChatGPT—they’ll be…

📌 How Do Grayscale Images Affect Visual Anomaly Detection? 🗂 Category: COMPUTER VISION 🕒 Date: 2025-07-24 | ⏱️ Read time:
📌 How Do Grayscale Images Affect Visual Anomaly Detection? 🗂 Category: COMPUTER VISION 🕒 Date: 2025-07-24 | ⏱️ Read time: 7 min read A practical exploration focusing on performance and speed

📌 Getting AI Discovery Right 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-07-24 | ⏱️ Read time: 17 min read A guide to
📌 Getting AI Discovery Right 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-07-24 | ⏱️ Read time: 17 min read A guide to ideating, validating, and prioritizing your AI use cases

📌 When 50/50 Isn’t Optimal: Debunking Even Rebalancing 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-07-24 | ⏱️ Read time: 7 m
📌 When 50/50 Isn’t Optimal: Debunking Even Rebalancing 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-07-24 | ⏱️ Read time: 7 min read A new theory of class imbalance demonstrates that the optimal training imbalance in a binary…

📌 How I Fine-Tuned Granite-Vision 2B to Beat a 90B Model — Insights and Lessons Learned 🗂 Category: ARTIFICIAL INTELLIGENCE
📌 How I Fine-Tuned Granite-Vision 2B to Beat a 90B Model — Insights and Lessons Learned 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-07-25 | ⏱️ Read time: 24 min read A hands-on journey exploring fine-tuning techniques that unlock the power of small vision models.

📌 What Is a Query Folding in Power BI and Why should You Care? 🗂 Category: DATA ANALYSIS 🕒 Date: 2025-07-25 | ⏱️ Read time
📌 What Is a Query Folding in Power BI and Why should You Care? 🗂 Category: DATA ANALYSIS 🕒 Date: 2025-07-25 | ⏱️ Read time: 21 min read “Will that break a query folding?” “Does your query fold?”… Maybe someone asked you those…

📌 Declarative and Imperative Prompt Engineering for Generative AI 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-07-25 |
📌 Declarative and Imperative Prompt Engineering for Generative AI 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-07-25 | ⏱️ Read time: 9 min read Conceptual overview and practical considerations

📌 End-to-End AWS RDS Setup with Bastion Host Using Terraform 🗂 Category: DATA SCIENCE 🕒 Date: 2025-07-28 | ⏱️ Read time: 1
📌 End-to-End AWS RDS Setup with Bastion Host Using Terraform 🗂 Category: DATA SCIENCE 🕒 Date: 2025-07-28 | ⏱️ Read time: 11 min read Learn how to automate secure AWS infrastructure using Terraform — including VPC, public/private subnets, a…

📌 Talk to my Agent 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-07-28 | ⏱️ Read time: 9 min read The exciting new worl
📌 Talk to my Agent 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-07-28 | ⏱️ Read time: 9 min read The exciting new world of designing conversation driven APIs for LLMs.

📌 The Stanford Framework That Turns AI into Your PM Superpower 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-07-28 | ⏱️ Read t
📌 The Stanford Framework That Turns AI into Your PM Superpower 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-07-28 | ⏱️ Read time: 6 min read A human-centric guide to AI automation for product managers.

📌 Mastering NLP with spaCY — Part 1 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-07-29 | ⏱️ Read time: 6 min read Lear
📌 Mastering NLP with spaCY — Part 1 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-07-29 | ⏱️ Read time: 6 min read Learn about tokenization, lemmatization and the core operations.

📌 Physics-Informed Neural Networks for Inverse PDE Problems 🗂 Category: PHYSICS 🕒 Date: 2025-07-29 | ⏱️ Read time: 11 min
📌 Physics-Informed Neural Networks for Inverse PDE Problems 🗂 Category: PHYSICS 🕒 Date: 2025-07-29 | ⏱️ Read time: 11 min read Solving the Heat Equation using DeepXDE.

📌 How to Evaluate Graph Retrieval in MCP Agentic Systems 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-07-29 | ⏱️ Read
📌 How to Evaluate Graph Retrieval in MCP Agentic Systems 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-07-29 | ⏱️ Read time: 9 min read A framework for measuring retrieval quality in Model Context Protocol agents.