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 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

40 222

📌 How to Choose the Best ML Deployment Strategy: Cloud vs. Edge 🗂 Category: 🕒 Date: 2024-10-14 | ⏱️ Read time: 17 min read The choice between cloud and edge deployment could make or break your project

40 222

📌 Evaluating synthetic data 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-10-14 | ⏱️ Read time: 9 min read Assessing plausibility and usefulness of data we generated from real data

40 222

📌 AI Feels Easier Than Ever, But Is It Really? 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-10-15 | ⏱️ Read time: 9 min read The 4 big challenges of building AI products

40 222

📌 I Built An AI Human-Level Game Player 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-10-15 | ⏱️ Read time: 13 min read Old-school game trees can be incredibly effective.

40 222

📌 Dataflow architecture 🗂 Category: DATA ENGINEERING 🕒 Date: 2024-10-15 | ⏱️ Read time: 23 min read on derived data views and eventual consistency

40 222

📌 I Fine-Tuned the Tiny Llama 3.2 1B to Replace GPT-4o 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-15 | ⏱️ Read time: 8 min read Is the fine-tuning effort worth more than few-shot prompting?

40 222

📌 Continual Learning: A Primer 🗂 Category: DEEP LEARNING 🕒 Date: 2024-10-15 | ⏱️ Read time: 8 min read Plus paper recommendations

40 222

📌 Normalized Discounted Cumulative Gain (NDCG) – The Ultimate Ranking Metric 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-15 | ⏱️ Read time: 10 min read NDCG – The Rank-Aware Metric for Evaluating Recommendation Systems

40 222

📌 Will Your Vote Decide the Next President? 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-15 | ⏱️ Read time: 22 min read Simulating the probability that your singular vote swings the election in November

40 222

📌 Beyond Naive RAG: Advanced Techniques for Building Smarter and Reliable AI Systems 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2024-10-16 | ⏱️ Read time: 32 min read A deep dive into advanced indexing, pre-retrieval, retrieval, and post-retrieval techniques to enhance RAG performance

40 222

📌 Marketing Mix Modeling (MMM): How to Avoid Biased Channel Estimates 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-16 | ⏱️ Read time: 16 min read Learn which variables you should and should not take into account in your model.

40 222

📌 The Science Behind AI’s First Nobel Prize 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-10-16 | ⏱️ Read time: 13 min read How Physics and Machine Learning Joined Forces to Win Physics Nobel 2024

40 222

📌 Exploring DRESS Kit V2 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-10-16 | ⏱️ Read time: 13 min read Exploring new features and notable changes in the latest version of the DRESS Kit

40 222

📌 A Novel Approach to Detect Coordinated Attacks Using Clustering 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-10-16 | ⏱️ Read time: 18 min read Unveiling hidden patterns: grouping malicious behavior

40 222

📌 Visualization of Data with Pie Charts in Matplotlib 🗂 Category: 🕒 Date: 2024-10-16 | ⏱️ Read time: 5 min read Examples of how to create different types of pie charts using Matplotlib to visualize the…

40 222

📌 Temporal-Difference Learning: Combining Dynamic Programming and Monte Carlo Methods for Reinforcement Learning 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-10-17 | ⏱️ Read time: 17 min read Milestones of RL: Q-Learning and Double Q-Learning

40 222

📌 Create Your Own Prompt Enhancer from Scratch 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-10-17 | ⏱️ Read time: 11 min read How to emulate OpenAI’s system prompt generator functionality

40 222

📌 Fine-Tuning BERT for Text Classification 🗂 Category: DEEP LEARNING 🕒 Date: 2024-10-17 | ⏱️ Read time: 6 min read A hackable example with Python code

40 222

📌 All You Need to Know to Build Radial Charts in Tableau 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-17 | ⏱️ Read time: 7 min read You will never forget it after this!

40 222

📌 A Critical Look at AI Image Generation 🗂 Category: ART 🕒 Date: 2024-10-17 | ⏱️ Read time: 12 min read What does image generative AI really tell us about our world?