Machine Learning

Open in Telegram

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 Syria228 Technologies & Applications3 352...

📈 Analytical overview of Telegram channel Machine Learning

Channel Machine Learning (@machinelearning9) in the English language segment is an active participant. Currently, the community unites 40 205 subscribers, ranking 3 352 in the Technologies & Applications category and 228 in the Syria region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 40 205 subscribers.

According to the latest data from 02 July, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 343 over the last 30 days and by 10 over the last 24 hours, overall reach remains high.

Verification status: Not verified
Engagement rate (ER): The average audience engagement rate is 1.99%. Within the first 24 hours after publication, content typically collects 2.28% reactions from the total number of subscribers.
Post reach: On average, each post receives 800 views. Within the first day, a publication typically gains 915 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 03 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.

40 205

Subscribers

+1024 hours

+837 days

+34330 days

800

Post views

~ 91524 hours

~ 1 23548 hours

1.99%

Engagement rate

~ 3

Posts per day

Ads index

beta

Posts Archive

40 210

📌 TimesFM: The Boom of Foundation Models in Time Series Forecasting 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-09-20 | ⏱️ Read time: 14 min read Explore How Google’s Latest AI Model Delivers Zero-Shot Forecasting Accuracy Using Over 307 Billion Data…

40 210

📌 Topic Modelling Your Personal Data 🗂 Category: 🕒 Date: 2024-09-21 | ⏱️ Read time: 29 min read Using Traditional and Transformer Models to Explore Personal Data Stored by Brokers

40 210

📌 Reinforcement Learning, Part 8: Feature State Construction 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-09-21 | ⏱️ Read time: 17 min read Enhancing linear methods by smartly incorporating state features into the learning objective

40 210

“Nobody believed you could grow small capital—until I saw this.” $1,000 turned into real profit before my eyes. The secret? Bonus fuel & copytrading with Elite Gold. Want proof? See how it’s actually done before the bonus ends. #ad InsideAds

40 210

📌 A Basic Introduction to Quantum GANs 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-09-21 | ⏱️ Read time: 11 min read “Quantum computing just becomes vastly simpler once you take the physics out of it.”

40 210

📌 An Intuitive Guide to Integrate SQL and Python for Data Science 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-21 | ⏱️ Read time: 11 min read Learn to master MySQL connector, a Python library that enables to interact with MYSQL database

40 210

📌 Proxy SHAP: Speed Up Explainability with Simpler Models 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-21 | ⏱️ Read time: 7 min read A Practical Guide to Efficient SHAP Computation

40 210

📌 The Machine Learning Lessons I’ve Learned This Month 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-09-30 | ⏱️ Read time: 7 min read September 2025: library or self-made, Ditto and Launchbar, reading widely and deeply

40 210

📌 How to Build Effective Agentic Systems with LangGraph 🗂 Category: AGENTIC AI 🕒 Date: 2025-09-30 | ⏱️ Read time: 12 min read Create AI workflows with agentic frameworks

40 210

📌 Actual Intelligence in the Age of AI 🗂 Category: AUTHOR SPOTLIGHTS 🕒 Date: 2025-09-30 | ⏱️ Read time: 11 min read Jarom Hulet on mastering fundamentals, hiring well, and deciding what to write about next

40 210

📌 Beyond ROC-AUC and KS: The Gini Coefficient, Explained Simply 🗂 Category: DATA SCIENCE 🕒 Date: 2025-09-30 | ⏱️ Read time: 7 min read Understanding Gini and Lorenz curves for smarter model evaluation

40 210

Repost from Machine Learning with Python

This channels is for Programmers, Coders, Software Engineers. 0️⃣ Python 1️⃣ Data Science 2️⃣ Machine Learning 3️⃣ Data Visualization 4️⃣ Artificial Intelligence 5️⃣ Data Analysis 6️⃣ Statistics 7️⃣ Deep Learning 8️⃣ programming Languages ✅ https://t.me/addlist/8_rRW2scgfRhOTc0 ✅ https://t.me/Codeprogrammer

40 210

Ever wondered why the same grape can taste wildly different from one bottle to another? The answer lies in the secrets of terroir, winemaking, and those rare finds only true wine lovers discover. Unlock a world of honest reviews, tasting notes, and hidden gems—subscribe to Simply Wine | Great Wine Lover and turn every glass into a new adventure! #ad InsideAds

40 210

📌 Hands-On Numerical Derivative with Python, from Zero to Hero 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-22 | ⏱️ Read time: 10 min read Here’s everything you need to know (beyond the standard definition) to master the numerical derivative…

40 210

📌 How I Deal with Hallucinations at an AI Startup 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-09-22 | ⏱️ Read time: 8 min read And the difference between weak vs strong grounding

40 210

📌 Data Empowers Business 🗂 Category: DATA ENGINEERING 🕒 Date: 2024-09-22 | ⏱️ Read time: 10 min read Exploiting the full potential of universal data supply

40 210

📌 Build Your Agents from Scratch 🗂 Category: 🕒 Date: 2024-09-23 | ⏱️ Read time: 8 min read Design your own agents without any framework

40 210

📌 Embeddings Are Kind of Shallow 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2024-09-23 | ⏱️ Read time: 33 min read What I learned doing semantic search on U.S. Presidents with four language model embeddings

40 210

📌 Programming an Arduino with CrewAI Agents 🗂 Category: PROGRAMMING 🕒 Date: 2024-09-23 | ⏱️ Read time: 7 min read An interaction between electronics and LLMs

40 210

📌 Breaking It Down : Chunking Techniques for Better RAG 🗂 Category: 🕒 Date: 2024-09-23 | ⏱️ Read time: 19 min read Mastering chunking for efficient retrieval in RAG systems