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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 40 373 subscribers, ranking 3 327 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 40 373 subscribers.

According to the latest data from 12 July, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 399 over the last 30 days and by 24 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 2.42%. 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 979 views. Within the first day, a publication typically gains 703 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 13 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.

40 373
Subscribers
+2424 hours
+1257 days
+39930 days
Posts Archive
📌 AI FOMO, Shadow AI, and Other Business Problems 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-09-03 | ⏱️ Read time: 6
📌 AI FOMO, Shadow AI, and Other Business Problems 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-09-03 | ⏱️ Read time: 6 min read What’s the state of AI in business these days, and how much does it cost…

📌 Useful Python Libraries You Might Not Have Heard Of: Freezegun 🗂 Category: PROGRAMMING 🕒 Date: 2025-09-03 | ⏱️ Read time
📌 Useful Python Libraries You Might Not Have Heard Of:  Freezegun 🗂 Category: PROGRAMMING 🕒 Date: 2025-09-03 | ⏱️ Read time: 12 min read Bring time to a standstill in your Python tests

📌 The Programming Skills You Need for Today’s Data Roles 🗂 Category: THE VARIABLE 🕒 Date: 2025-09-04 | ⏱️ Read time: 3 min
📌 The Programming Skills You Need for Today’s Data Roles 🗂 Category: THE VARIABLE 🕒 Date: 2025-09-04 | ⏱️ Read time: 3 min read How to stand out in a crowded field

📌 Boosting Your Anomaly Detection With LLMs 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-09-04 | ⏱️ Read time: 17 min re
📌 Boosting Your Anomaly Detection With LLMs 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-09-04 | ⏱️ Read time: 17 min read The 7 emerging application patterns you should know

📌 Using LangGraph and MCP Servers to Create My Own Voice Assistant 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-09-04 | ⏱️ Re
📌 Using LangGraph and MCP Servers to Create My Own Voice Assistant 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-09-04 | ⏱️ Read time: 30 min read Built over 14 days, all locally run, no API keys, cloud services, or subscription fees.

📌 MobileNetV1 Paper Walkthrough: The Tiny Giant 🗂 Category: DEEP LEARNING 🕒 Date: 2025-09-04 | ⏱️ Read time: 26 min read U
📌 MobileNetV1 Paper Walkthrough: The Tiny Giant 🗂 Category: DEEP LEARNING 🕒 Date: 2025-09-04 | ⏱️ Read time: 26 min read Understanding and implementing MobileNetV1 from scratch with PyTorch

📌 A Visual Guide to Tuning Random Forest Hyperparameters 🗂 Category: DATA SCIENCE 🕒 Date: 2025-09-04 | ⏱️ Read time: 8 min
📌 A Visual Guide to Tuning Random Forest Hyperparameters 🗂 Category: DATA SCIENCE 🕒 Date: 2025-09-04 | ⏱️ Read time: 8 min read How hyperparameter tuning visually changes random forests

📌 Should We Use LLMs As If They Were Swiss Knives? 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-09-04 | ⏱️ Read time:
📌 Should We Use LLMs As If They Were Swiss Knives? 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-09-04 | ⏱️ Read time: 9 min read A logic game performance comparison between popular LLMs and a custom-made algorithm

📌 Tool Masking: The Layer MCP Forgot 🗂 Category: AGENTIC AI 🕒 Date: 2025-09-05 | ⏱️ Read time: 16 min read Tool masking fo
📌 Tool Masking: The Layer MCP Forgot 🗂 Category: AGENTIC AI 🕒 Date: 2025-09-05 | ⏱️ Read time: 16 min read Tool masking for AI improves AI agents: shape MCP tool surfaces to cut tokens and…

📌 Zero-Inflated Data: A Comparison of Regression Models 🗂 Category: DATA SCIENCE 🕒 Date: 2025-09-05 | ⏱️ Read time: 13 min
📌 Zero-Inflated Data: A Comparison of Regression Models 🗂 Category: DATA SCIENCE 🕒 Date: 2025-09-05 | ⏱️ Read time: 13 min read How to detect it and which model to choose.

📌 AI Operations Under the Hood: Challenges and Best Practices 🗂 Category: LLM APPLICATIONS 🕒 Date: 2025-09-05 | ⏱️ Read ti
📌 AI Operations Under the Hood: Challenges and Best Practices 🗂 Category: LLM APPLICATIONS 🕒 Date: 2025-09-05 | ⏱️ Read time: 18 min read Building robust, reproducible, and reliable GenAI applications requires a framework of continuous improvement, rigorous evaluation,…

📌 Showcasing Your Work on HuggingFace Spaces 🗂 Category: PRODUCTIVITY 🕒 Date: 2025-09-05 | ⏱️ Read time: 9 min read Buildi
📌 Showcasing Your Work on HuggingFace Spaces 🗂 Category: PRODUCTIVITY 🕒 Date: 2025-09-05 | ⏱️ Read time: 9 min read Building an app is exciting – but sharing it is where the real value kicks…

📌 How to Context Engineer to Optimize Question Answering Pipelines 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-09-05 |
📌 How to Context Engineer to Optimize Question Answering Pipelines 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-09-05 | ⏱️ Read time: 9 min read Learn how to apply context engineering to enhance your question answering systems.

📌 AI FOMO, Shadow AI, and Other Business Problems 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-09-03 | ⏱️ Read time: 6
📌 AI FOMO, Shadow AI, and Other Business Problems 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-09-03 | ⏱️ Read time: 6 min read What’s the state of AI in business these days, and how much does it cost…

📌 Useful Python Libraries You Might Not Have Heard Of: Freezegun 🗂 Category: PROGRAMMING 🕒 Date: 2025-09-03 | ⏱️ Read time
📌 Useful Python Libraries You Might Not Have Heard Of:  Freezegun 🗂 Category: PROGRAMMING 🕒 Date: 2025-09-03 | ⏱️ Read time: 12 min read Bring time to a standstill in your Python tests

📌 The Programming Skills You Need for Today’s Data Roles 🗂 Category: THE VARIABLE 🕒 Date: 2025-09-04 | ⏱️ Read time: 3 min
📌 The Programming Skills You Need for Today’s Data Roles 🗂 Category: THE VARIABLE 🕒 Date: 2025-09-04 | ⏱️ Read time: 3 min read How to stand out in a crowded field

📌 Boosting Your Anomaly Detection With LLMs 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-09-04 | ⏱️ Read time: 17 min re
📌 Boosting Your Anomaly Detection With LLMs 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-09-04 | ⏱️ Read time: 17 min read The 7 emerging application patterns you should know

📌 Using LangGraph and MCP Servers to Create My Own Voice Assistant 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-09-04 | ⏱️ Re
📌 Using LangGraph and MCP Servers to Create My Own Voice Assistant 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-09-04 | ⏱️ Read time: 30 min read Built over 14 days, all locally run, no API keys, cloud services, or subscription fees.

📌 MobileNetV1 Paper Walkthrough: The Tiny Giant 🗂 Category: DEEP LEARNING 🕒 Date: 2025-09-04 | ⏱️ Read time: 26 min read U
📌 MobileNetV1 Paper Walkthrough: The Tiny Giant 🗂 Category: DEEP LEARNING 🕒 Date: 2025-09-04 | ⏱️ Read time: 26 min read Understanding and implementing MobileNetV1 from scratch with PyTorch

📌 A Visual Guide to Tuning Random Forest Hyperparameters 🗂 Category: DATA SCIENCE 🕒 Date: 2025-09-04 | ⏱️ Read time: 8 min
📌 A Visual Guide to Tuning Random Forest Hyperparameters 🗂 Category: DATA SCIENCE 🕒 Date: 2025-09-04 | ⏱️ Read time: 8 min read How hyperparameter tuning visually changes random forests