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

Network:Machine Learning with Python Syria228 Technologies & Applications3 344...

📈 Analytical overview of Telegram channel Machine Learning

Channel Machine Learning (@machinelearning9) in the English language segment is an active participant. Currently, the community unites 40 221 subscribers, ranking 3 344 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 40 221 subscribers.

According to the latest data from 03 July, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 338 over the last 30 days and by 9 over the last 24 hours, overall reach remains high.

Verification status: Not verified
Engagement rate (ER): The average audience engagement rate is 2.04%. Within the first 24 hours after publication, content typically collects 2.42% reactions from the total number of subscribers.
Post reach: On average, each post receives 822 views. Within the first day, a publication typically gains 973 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 04 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.

40 221

Subscribers

+924 hours

+727 days

+33830 days

822

Post views

~ 97324 hours

~ 1 32148 hours

2.04%

Engagement rate

~ 3

Posts per day

Ads index

beta

Posts Archive

40 223

📌 Cognitive Prompting in LLMs 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-10-19 | ⏱️ Read time: 9 min read Can we teach machines to think like humans?

40 223

📌 The One Mindset Change That Launched Me into Data Science 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-19 | ⏱️ Read time: 13 min read Make it happen: tiny changes to break into data science or any dream career

40 223

📌 How Much Stress Can Your Server Handle When Self-Hosting LLMs? 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-19 | ⏱️ Read time: 7 min read Do you need more GPUs or a modern GPU? How do you make infrastructure decisions?

40 223

📌 Understanding LLMs from Scratch Using Middle School Math 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-10-19 | ⏱️ Read time: 52 min read In this article, we talk about how LLMs work, from scratch – assuming only that…

40 223

📌 How to Get Started on Your Data Science Career Journey 🗂 Category: CAREER ADVICE 🕒 Date: 2024-10-20 | ⏱️ Read time: 6 min read Six considerations for beginners to pick a resource for upskilling in Data Science and AI/ML

40 223

📌 AI Model Optimization on AWS Inferentia and Trainium 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-10-20 | ⏱️ Read time: 11 min read Tips for accelerating ML with AWS Neuron SDK

40 223

📌 ETL Pipelines in Python: Best Practices and Techniques 🗂 Category: DATA ENGINEERING 🕒 Date: 2024-10-20 | ⏱️ Read time: 12 min read Strategies for Enhancing Generalizability, Scalability, and Maintainability in Your ETL Pipelines

40 223

📌 Introducing the AI-3P Assessment Framework: Score AI Projects Before Committing Resources 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-09-24 | ⏱️ Read time: 13 min read A question-driven scorecard to prioritize and de-risk AI initiatives before implementation

40 223

📌 PyTorch Explained: From Automatic Differentiation to Training Custom Neural Networks 🗂 Category: DEEP LEARNING 🕒 Date: 2025-09-24 | ⏱️ Read time: 15 min read Deep learning is shaping our world as we speak. In fact, it has been slowly…

40 223

📌 RAG Explained: Reranking for Better Answers 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-09-24 | ⏱️ Read time: 10 min read How reranking improves retrieval-augmented generation by surfacing the most relevant results

40 223

📌 Decoding Nonlinear Signals In Large Observational Datasets 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-09-24 | ⏱️ Read time: 28 min read Rain, snow, or something In between?

40 223

📌 Carving out your competitive advantage with AI 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-10-17 | ⏱️ Read time: 15 min read Why the future of AI isn’t just automation – It’s craftsmanship, strategy, and innovation

40 223

📌 What Does It Take to Get Your Foot in the Door as a Data Scientist? 🗂 Category: CAREER ADVICE 🕒 Date: 2024-10-17 | ⏱️ Read time: 4 min read Our weekly selection of must-read Editors’ Picks and original features

40 223

📌 Integrating Multimodal Data into a Large Language Model 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2024-10-17 | ⏱️ Read time: 18 min read Developing a context-retrieval, multimodal RAG using advanced parsing, semantic & keyword search, and re-ranking

40 223

📌 GraphMuse: A Python Library for Symbolic Music Graph Processing 🗂 Category: DEEP LEARNING 🕒 Date: 2024-10-17 | ⏱️ Read time: 12 min read Yes, music and graphs do mix!

40 223

📌 Autoencoders: An Ultimate Guide for Data Scientists 🗂 Category: DEEP LEARNING 🕒 Date: 2024-10-17 | ⏱️ Read time: 25 min read A beginner’s guide to the architecture, Python implementation, and a glimpse into the future

40 223

📌 Why You Should Be Hiring Methodologists 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-17 | ⏱️ Read time: 6 min read “All you need to do is develop your mind. If you have thought deeply, nearly…

40 223

📌 How to Export a Stata “Notebook” to HTML 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-17 | ⏱️ Read time: 9 min read Create a shareable HTML document with your code, outputs, and graphs

40 223

📌 Reinforcement Learning for Physics: ODEs and Hyperparameter Tuning 🗂 Category: PHYSICS 🕒 Date: 2024-10-17 | ⏱️ Read time: 13 min read Controlling differential equations with gymnasium and optimizing algorithm hyperparameters

40 223

📌 What are Digital Twins? 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-10-18 | ⏱️ Read time: 7 min read Bridging the physical and digital worlds