Available now! Telegram Research 2025 β the year's key insights 
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
Show moreπ Analytical overview of Telegram channel Machine Learning
Channel Machine Learning (@machinelearning9) in the English language segment is an active participant. Currently, the community unites 40 150 subscribers, ranking 3 364 in the Technologies & Applications category and 227 in the Syria region.
π Audience metrics and dynamics
Since its creation on Π½Π΅Π²ΡΠ΄ΠΎΠΌΠΎ, the project has demonstrated rapid growth, gathering an audience of 40 150 subscribers.
According to the latest data from 27 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 412 over the last 30 days and by 5 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 1.96%. Within the first 24 hours after publication, content typically collects 1.89% reactions from the total number of subscribers.
- Post reach: On average, each post receives 785 views. Within the first day, a publication typically gains 760 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 2.
- Thematic interests: Content is focused on key topics such as distance, insidead, gpu, learning, degree.
π Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
βReal Machine Learning β simple, practical, and built on experience.
Learn step by step with clear explanations and working code.
Admin: @HusseinSheikho || @Hussein_Sheikhoβ
Thanks to the high frequency of updates (latest data received on 28 June, 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.
40 150
Subscribers
+524 hours
+1067 days
+41230 days
Posts Archive
40 150
π How I Used Machine Learning to Predict 41% of Project Delays Before They Happened
π Category: PROJECT MANAGEMENT
π Date: 2025-10-17 | β±οΈ Read time: 12 min read
How data science can help project managers anticipate risks and save time
40 150
π How to Classify Lung Cancer Subtype from DNA Copy Numbers Using PyTorch
π Category: DEEP LEARNING
π Date: 2025-10-17 | β±οΈ Read time: 12 min read
A step-by-step introduction to understanding cancer from the perspective of a data scientist.
40 150
π Machine Learning Meets Panel Data: What Practitioners Need to Know
π Category: MACHINE LEARNING
π Date: 2025-10-17 | β±οΈ Read time: 8 min read
How to avoid overestimating machine learning modelsβ performance, usefulness, and real-world applicability due to hiddenβ¦
40 150
π€π§ Sora: OpenAIβs Breakthrough Text-to-Video Model Transforming Visual Creativity
ποΈ 18 Oct 2025
π AI News & Trends
Introduction Artificial Intelligence (AI) is rapidly transforming the creative world. From generating realistic images to composing music and writing code, AI has redefined how humans interact with technology. But one of the most revolutionary advancements in this domain is Sora, OpenAIβs text-to-video generative model that converts written prompts into hyper-realistic video clips. Ithas captured global ...
#Sora #OpenAI #TextToVideo #AI #VisualCreativity #GenerativeModel
40 150
π€π§ Sora: OpenAIβs Breakthrough Text-to-Video Model Transforming Visual Creativity
ποΈ 18 Oct 2025
π AI News & Trends
Introduction Artificial Intelligence (AI) is rapidly transforming the creative world. From generating realistic images to composing music and writing code, AI has redefined how humans interact with technology. But one of the most revolutionary advancements in this domain is Sora, OpenAIβs text-to-video generative model that converts written prompts into hyper-realistic video clips. Ithas captured global ...
#Sora #OpenAI #TextToVideo #AI #VisualCreativity #GenerativeModel
40 150
π Learnings from a Machine Learning Engineer β Part 2: The Data Sets
π Category: MACHINE LEARNING
π Date: 2025-02-13 | β±οΈ Read time: 10 min read
In Part 1, we discussed the importance of collecting good image data and assigning proper labelsβ¦
40 150
π Learnings from a Machine Learning Engineer β Part 4: The Model
π Category: MACHINE LEARNING
π Date: 2025-02-13 | β±οΈ Read time: 8 min read
In this latest part of my series, I will share what I have learned onβ¦
40 150
π Learnings from a Machine Learning Engineer β Part 1: The Data
π Category: MACHINE LEARNING
π Date: 2025-02-13 | β±οΈ Read time: 13 min read
It is said that in order for a machine learning model to be successful, youβ¦
40 150
π Learnings from a Machine Learning Engineer β Part 3: The Evaluation
π Category: MACHINE LEARNING
π Date: 2025-02-13 | β±οΈ Read time: 13 min read
In this third part of my series, I will explore the evaluation process which isβ¦
40 150
π Learnings from a Machine Learning Engineer β Part 5: The Training
π Category: MACHINE LEARNING
π Date: 2025-02-13 | β±οΈ Read time: 16 min read
In this fifth part of my series, I will outline the steps for creating aβ¦
40 150
π Building a Data Engineering Center of Excellence
π Category: DATA ENGINEERING
π Date: 2025-02-13 | β±οΈ Read time: 11 min read
As data continues to grow in importance and become more complex, the need for skilledβ¦
40 150
Repost from Machine Learning with Python
AI Engineering roadmap that beginners can actually follow. Everything is based on 100% free, open-source, and community resources
All resources can be found here: GitHub
π @codeprogrammer
40 150
βI was blocked on Telegram at 2 AM and thought it was over. But then I found THIS.β
Everyoneβs missing out on the one-click PROXY that just saved my chats. See the link β unlock Telegram when you need it most!
#ad InsideAds
40 150
π Analyzing Lake Mendota Ice Phenology with Python
π Category: CLIMATE CHANGE
π Date: 2024-06-10 | β±οΈ Read time: 10 min read
An analysis-ready dataset you can use right now
40 150
π Task-Aware RAG Strategies for When Sentence Similarity Fails
π Category: DATA SCIENCE
π Date: 2024-06-10 | β±οΈ Read time: 19 min read
When retrieval is based on an additional metric besides just sentence similarity, traditional methods performβ¦
40 150
π€π§ Agentic Entropy-Balanced Policy Optimization (AEPO): Balancing Exploration and Stability in Reinforcement Learning for Web Agents
ποΈ 17 Oct 2025
π AI News & Trends
AEPO (Agentic Entropy-Balanced Policy Optimization) represents a major advancement in the evolution of Agentic Reinforcement Learning (RL). As large language models (LLMs) increasingly act as autonomous web agents β searching, reasoning and interacting with tools β the need for balanced exploration and stability has become crucial. Traditional RL methods often rely heavily on entropy to ...
#AgenticRL #ReinforcementLearning #LLMs #WebAgents #EntropyBalanced #PolicyOptimization
40 150
π Spatial Index: Space-Filling Curves
π Category: DATABASE DESIGN
π Date: 2024-06-11 | β±οΈ Read time: 11 min read
Spatial Index and Space Filling Curves for Multi-dimensional data
40 150
π Reinforcement Learning, Part 4: Monte Carlo Control
π Category: DATA SCIENCE
π Date: 2024-06-11 | β±οΈ Read time: 17 min read
Harnessing Monte Carlo algorithms to discover the best strategies
40 150
π Anatomy of Windows Functions
π Category: DATA ENGINEERING
π Date: 2024-06-11 | β±οΈ Read time: 15 min read
Theory and practice of an underappreciated SQL operation
40 150
π SQL Explained: Ranking Analytics
π Category: DATA ENGINEERING
π Date: 2024-06-11 | β±οΈ Read time: 11 min read
What they are and how you use them
