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Machine Learning

Machine Learning

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

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πŸ“ˆ Analytical overview of Telegram channel Machine Learning

Channel Machine Learning (@machinelearning9) in the English language segment is an active participant. Currently, the community unites 40 265 subscribers, ranking 3 343 in the Technologies & Applications category and 227 in the Syria region.

πŸ“Š Audience metrics and dynamics

Since its creation on Π½Π΅Π²Ρ–Π΄ΠΎΠΌΠΎ, the project has demonstrated rapid growth, gathering an audience of 40 265 subscribers.

According to the latest data from 06 July, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 336 over the last 30 days and by -4 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 2.25%. Within the first 24 hours after publication, content typically collects 1.88% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 906 views. Within the first day, a publication typically gains 758 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.

πŸ“ Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
β€œReal Machine Learning β€” 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 07 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.

40 265
Subscribers
-424 hours
+917 days
+33630 days
Posts Archive
πŸ“Œ The Multi-Armed Bandit Problem-A Beginner-Friendly Guide πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-12-23 | ⏱️ Read time: 6 m
πŸ“Œ The Multi-Armed Bandit Problem-A Beginner-Friendly Guide πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-12-23 | ⏱️ Read time: 6 min read Understanding the exploitation-exploration trade-off with an example

πŸ“Œ Advanced Prompt Engineering: Chain of Thought (CoT) πŸ—‚ Category: LARGE LANGUAGE MODELS πŸ•’ Date: 2024-12-23 | ⏱️ Read time:
πŸ“Œ Advanced Prompt Engineering: Chain of Thought (CoT) πŸ—‚ Category: LARGE LANGUAGE MODELS πŸ•’ Date: 2024-12-23 | ⏱️ Read time: 26 min read Comparing different techniques for reasoning

πŸ“Œ How to Clean Your Data for Your Real-Life Data Science Projects πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-12-23 | ⏱️ Read ti
πŸ“Œ How to Clean Your Data for Your Real-Life Data Science Projects πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-12-23 | ⏱️ Read time: 7 min read How I treat missing values-with a quick Python Guide

πŸ“Œ How to Tackle an Optimization Problem with Constraint Programming πŸ—‚ Category: πŸ•’ Date: 2024-12-23 | ⏱️ Read time: 7 min r
πŸ“Œ How to Tackle an Optimization Problem with Constraint Programming πŸ—‚ Category: πŸ•’ Date: 2024-12-23 | ⏱️ Read time: 7 min read Case study: the travelling salesman problem

πŸ“Œ Classifier-free guidance for LLMs performance enhancing πŸ—‚ Category: MACHINE LEARNING πŸ•’ Date: 2024-12-23 | ⏱️ Read time:
πŸ“Œ Classifier-free guidance for LLMs performance enhancing πŸ—‚ Category: MACHINE LEARNING πŸ•’ Date: 2024-12-23 | ⏱️ Read time: 14 min read Check and improve classifier-free guidance for text generation large language models. While participating in NeurIPS…

πŸ“Œ How Bias and Variance Affect Your Model πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-12-24 | ⏱️ Read time: 7 min read Learn the
πŸ“Œ How Bias and Variance Affect Your Model πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-12-24 | ⏱️ Read time: 7 min read Learn the concepts and the practice. How a model behaves in each case.

πŸ“Œ I’ve Done 80+ Data Science Interviews – Here’s What Works πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-12-24 | ⏱️ Read time: 7
πŸ“Œ I’ve Done 80+ Data Science Interviews – Here’s What Works πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-12-24 | ⏱️ Read time: 7 min read 3 years of data science interview experience

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πŸ“Œ Design Patterns with Python for Machine Learning Engineers: Template Method πŸ—‚ Category: MACHINE LEARNING πŸ•’ Date: 2024-12
πŸ“Œ Design Patterns with Python for Machine Learning Engineers: Template Method πŸ—‚ Category: MACHINE LEARNING πŸ•’ Date: 2024-12-24 | ⏱️ Read time: 4 min read Learn how to use the Template design pattern to enhance your code

πŸ“Œ I’m Doing the Advent of Code 2024 in Python – Day 4 πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-12-24 | ⏱️ Read time: 6 min re
πŸ“Œ I’m Doing the Advent of Code 2024 in Python – Day 4 πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-12-24 | ⏱️ Read time: 6 min read Let’s see how many stars we’ll collect.

πŸ“Œ 2024 Survival Guide for Machine Learning Engineer Interviews πŸ—‚ Category: MACHINE LEARNING πŸ•’ Date: 2024-12-24 | ⏱️ Read t
πŸ“Œ 2024 Survival Guide for Machine Learning Engineer Interviews πŸ—‚ Category: MACHINE LEARNING πŸ•’ Date: 2024-12-24 | ⏱️ Read time: 17 min read A year-end summary for junior-level MLE interview preparation

πŸ“Œ Building a Custom AI Jira Agent πŸ—‚ Category: πŸ•’ Date: 2024-12-25 | ⏱️ Read time: 23 min read How I used Google Mesop, Djan
πŸ“Œ Building a Custom AI Jira Agent πŸ—‚ Category: πŸ•’ Date: 2024-12-25 | ⏱️ Read time: 23 min read How I used Google Mesop, Django, LangChain Agents, CO-STAR & Chain-of-Thought prompting combined with the…

πŸ“Œ Three Important Pandas Functions You Need to Know πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-12-25 | ⏱️ Read time: 6 min read
πŸ“Œ Three Important Pandas Functions You Need to Know πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-12-25 | ⏱️ Read time: 6 min read Master these techniques to stand out as a Python developer

πŸ“Œ Sensor Fusion – KITTI – β€˜Lidar-based Obstacle Detection’ – Part-1 πŸ—‚ Category: MACHINE LEARNING πŸ•’ Date: 2024-12-25 | ⏱️ R
πŸ“Œ Sensor Fusion – KITTI – β€˜Lidar-based Obstacle Detection’ – Part-1 πŸ—‚ Category: MACHINE LEARNING πŸ•’ Date: 2024-12-25 | ⏱️ Read time: 24 min read Sensor fusion, multi-modal perception, autonomous vehicles – if these keywords pique your interest, this Medium…

πŸ“Œ How to Become a Machine Learning Engineer (Step-by-Step) πŸ—‚ Category: MACHINE LEARNING πŸ•’ Date: 2025-09-15 | ⏱️ Read time:
πŸ“Œ How to Become a Machine Learning Engineer (Step-by-Step) πŸ—‚ Category: MACHINE LEARNING πŸ•’ Date: 2025-09-15 | ⏱️ Read time: 12 min read Your one-stop guide to becoming a machine learning engineer

πŸ“Œ Learn How to Use Transformers with HuggingFace and SpaCy πŸ—‚ Category: ARTIFICIAL INTELLIGENCE πŸ•’ Date: 2025-09-15 | ⏱️ Rea
πŸ“Œ Learn How to Use Transformers with HuggingFace and SpaCy πŸ—‚ Category: ARTIFICIAL INTELLIGENCE πŸ•’ Date: 2025-09-15 | ⏱️ Read time: 7 min read Mastering NLP with spaCy: Part 4

πŸ“Œ You Only Need 3 Things to Turn AI Experiments into AI Advantage πŸ—‚ Category: ARTIFICIAL INTELLIGENCE πŸ•’ Date: 2025-09-15 |
πŸ“Œ You Only Need 3 Things to Turn AI Experiments into AI Advantage πŸ—‚ Category: ARTIFICIAL INTELLIGENCE πŸ•’ Date: 2025-09-15 | ⏱️ Read time: 7 min read Trapped in a purgatory of POCs enterprises need to focus and build just 3 pillars…

πŸ“Œ Implementing the Coffee Machine Project in Python Using Object Oriented Programming πŸ—‚ Category: PROGRAMMING πŸ•’ Date: 2025
πŸ“Œ Implementing the Coffee Machine Project in Python Using Object Oriented Programming πŸ—‚ Category: PROGRAMMING πŸ•’ Date: 2025-09-15 | ⏱️ Read time: 9 min read Understanding classes, objects, attributes, and methods

πŸ“Œ A Visual Guide to Tuning Gradient Boosted Trees πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2025-09-15 | ⏱️ Read time: 10 min read
πŸ“Œ A Visual Guide to Tuning Gradient Boosted Trees πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2025-09-15 | ⏱️ Read time: 10 min read Introduction My previous posts looked at the bog-standard decision tree and the wonder of a…

πŸ“Œ Learning ML or Learning About Learning ML? πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2025-01-03 | ⏱️ Read time: 4 min read Pragma
πŸ“Œ Learning ML or Learning About Learning ML? πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2025-01-03 | ⏱️ Read time: 4 min read Pragmatism versus (over-)planning