en
Feedback
Machine Learning

Machine Learning

Open in Telegram

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

Show more

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 40 244 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 40 244 subscribers.

According to the latest data from 05 July, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 346 over the last 30 days and by 22 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 1.97%. Within the first 24 hours after publication, content typically collects 1.86% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 794 views. Within the first day, a publication typically gains 749 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 06 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.

40 244
Subscribers
+2224 hours
+987 days
+34630 days
Posts Archive
πŸ“Œ Demystifying the Correlation Matrix in Data Science πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-11-13 | ⏱️ Read time: 16 min r
πŸ“Œ Demystifying the Correlation Matrix in Data Science πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-11-13 | ⏱️ Read time: 16 min read Understanding the Connections Between Variables: A Comprehensive Guide to Correlation Matrices and Their Applications

πŸ“Œ Python Can Now Call Mojo πŸ—‚ Category: PROGRAMMING πŸ•’ Date: 2025-09-21 | ⏱️ Read time: 14 min read Boost your runtimes with
πŸ“Œ Python Can Now Call Mojo πŸ—‚ Category: PROGRAMMING πŸ•’ Date: 2025-09-21 | ⏱️ Read time: 14 min read Boost your runtimes with lightning-fast Mojo code

πŸ“Œ Data Visualization Explained: What It Is and Why It Matters πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2025-09-21 | ⏱️ Read time:
πŸ“Œ Data Visualization Explained: What It Is and Why It Matters πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2025-09-21 | ⏱️ Read time: 8 min read A brief introduction to data visualization and its importance in today’s technological landscape.

πŸ“Œ Building a Local Voice Assistant with LLMs and Neural Networks on Your CPU Laptop πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-
πŸ“Œ Building a Local Voice Assistant with LLMs and Neural Networks on Your CPU Laptop πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-11-19 | ⏱️ Read time: 6 min read A practical guide to run lightweight LLMs using python

πŸ“Œ 3 Triangle-Shaped Chart Ideas as Alternatives to Some Basic Charts πŸ—‚ Category: DATA VISUALIZATION πŸ•’ Date: 2024-11-19 | ⏱
πŸ“Œ 3 Triangle-Shaped Chart Ideas as Alternatives to Some Basic Charts πŸ—‚ Category: DATA VISUALIZATION πŸ•’ Date: 2024-11-19 | ⏱️ Read time: 8 min read Creating data visualizations with Python as alternatives to bar charts, pie charts, and some 3D…

πŸ“Œ How I Created a Data Science Project Following CRISP-DM Lifecycle πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-11-13 | ⏱️ Read
πŸ“Œ How I Created a Data Science Project Following CRISP-DM Lifecycle πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-11-13 | ⏱️ Read time: 26 min read An end-to-end project using the CRISP-DM framework

πŸ“Œ Awesome Plotly with Code Series (Part 4): Grouping Bars vs Multi-Coloured Bars πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-11-
πŸ“Œ Awesome Plotly with Code Series (Part 4): Grouping Bars vs Multi-Coloured Bars πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-11-14 | ⏱️ Read time: 13 min read Do technicolour bars really help make a story clear?

πŸ“Œ Writing LLMs in Rust: Looking for an Efficient Matrix Multiplication πŸ—‚ Category: ARTIFICIAL INTELLIGENCE πŸ•’ Date: 2024-11
πŸ“Œ Writing LLMs in Rust: Looking for an Efficient Matrix Multiplication πŸ—‚ Category: ARTIFICIAL INTELLIGENCE πŸ•’ Date: 2024-11-14 | ⏱️ Read time: 16 min read Here are the lessons I learned and how I am writing llm.rust and tackling the…

πŸ“Œ How To Up-Skill In Data Science πŸ—‚ Category: CAREER ADVICE πŸ•’ Date: 2024-11-14 | ⏱️ Read time: 7 min read My framework for
πŸ“Œ How To Up-Skill In Data Science πŸ—‚ Category: CAREER ADVICE πŸ•’ Date: 2024-11-14 | ⏱️ Read time: 7 min read My framework for continually becoming a better data scientist

πŸ“Œ Network Analysis, Diffusion Models, Data Lakehouses, and More: Our Best Recent Deep Dives πŸ—‚ Category: DATA SCIENCE πŸ•’ Dat
πŸ“Œ Network Analysis, Diffusion Models, Data Lakehouses, and More: Our Best Recent Deep Dives πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-11-14 | ⏱️ Read time: 4 min read Our weekly selection of must-read Editors’ Picks and original features

πŸ“Œ Why STEM Is Important for Any Data Scientist πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-11-14 | ⏱️ Read time: 8 min read 3 ca
πŸ“Œ Why STEM Is Important for Any Data Scientist πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-11-14 | ⏱️ Read time: 8 min read 3 cases to prove this from my own experience

πŸ“Œ Gradient Boosting Regressor, Explained: A Visual Guide with Code Examples πŸ—‚ Category: MACHINE LEARNING πŸ•’ Date: 2024-11-1
πŸ“Œ Gradient Boosting Regressor, Explained: A Visual Guide with Code Examples πŸ—‚ Category: MACHINE LEARNING πŸ•’ Date: 2024-11-14 | ⏱️ Read time: 14 min read Fitting to errors one booster stage at a time

πŸ“Œ Techniques for Chat Data Analytics with Python πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-11-15 | ⏱️ Read time: 11 min read P
πŸ“Œ Techniques for Chat Data Analytics with Python πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-11-15 | ⏱️ Read time: 11 min read Part II: Topic Extraction with BERTopic

πŸ“Œ Rewiring My Career: How I Transitioned from Electrical Engineering to Data Engineering πŸ—‚ Category: DATA ENGINEERING πŸ•’ Da
πŸ“Œ Rewiring My Career: How I Transitioned from Electrical Engineering to Data Engineering πŸ—‚ Category: DATA ENGINEERING πŸ•’ Date: 2024-11-15 | ⏱️ Read time: 12 min read Data is booming and so are the job opportunities in this field. A must read…

πŸ“Œ Field Boundary Detection in Satellite Imagery Using the SAM2 Model πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-11-15 | ⏱️ Read
πŸ“Œ Field Boundary Detection in Satellite Imagery Using the SAM2 Model πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-11-15 | ⏱️ Read time: 14 min read Step-by-Step Tutorial on Applying Segment Anything Model Version 2 to Satellite Imagery for Detecting and…

πŸ“Œ ROI Worship Can Be Bad For Business πŸ—‚ Category: BUSINESS πŸ•’ Date: 2024-11-15 | ⏱️ Read time: 8 min read Watch out for the
πŸ“Œ ROI Worship Can Be Bad For Business πŸ—‚ Category: BUSINESS πŸ•’ Date: 2024-11-15 | ⏱️ Read time: 8 min read Watch out for these three ways too much of a good thing can be dangerous

πŸ“Œ Introduction to the Finite Normal Mixtures in Regression with πŸ—‚ Category: πŸ•’ Date: 2024-11-15 | ⏱️ Read time: 8 min read
πŸ“Œ Introduction to the Finite Normal Mixtures in Regression with πŸ—‚ Category: πŸ•’ Date: 2024-11-15 | ⏱️ Read time: 8 min read In this post, we demonstrate how to simulate a finite mixture model for regression using…

πŸ“Œ Why Most Cross-Validation Visualizations Are Wrong (And How to Fix Them) πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-11-16 | ⏱
πŸ“Œ Why Most Cross-Validation Visualizations Are Wrong (And How to Fix Them) πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-11-16 | ⏱️ Read time: 12 min read Stop using moving boxes!

πŸ“Œ Open the Artificial Brain: Sparse Autoencoders for LLM Inspection πŸ—‚ Category: ARTIFICIAL INTELLIGENCE πŸ•’ Date: 2024-11-16
πŸ“Œ Open the Artificial Brain: Sparse Autoencoders for LLM Inspection πŸ—‚ Category: ARTIFICIAL INTELLIGENCE πŸ•’ Date: 2024-11-16 | ⏱️ Read time: 15 min read A deep dive into LLM visualization and interpretation using sparse autoencoders

πŸ“Œ Exploring Music Transcription with Multi-Modal Language Models πŸ—‚ Category: ARTIFICIAL INTELLIGENCE πŸ•’ Date: 2024-11-17 |
πŸ“Œ Exploring Music Transcription with Multi-Modal Language Models πŸ—‚ Category: ARTIFICIAL INTELLIGENCE πŸ•’ Date: 2024-11-17 | ⏱️ Read time: 21 min read Using Qwen2-Audio to transcribe music into sheet music