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Machine Learning

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

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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 40 191 subscribers, ranking 3 381 in the Technologies & Applications category and 228 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 40 191 subscribers.

According to the latest data from 01 July, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 355 over the last 30 days and by 21 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 2.12% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 818 views. Within the first day, a publication typically gains 851 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.

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 02 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.

40 191
Subscribers
+2124 hours
+857 days
+35530 days
Posts Archive
πŸ“Œ Reinforcement Learning for Physical Dynamical Systems: An Alternative Approach πŸ—‚ Category: MACHINE LEARNING πŸ•’ Date: 2024
πŸ“Œ Reinforcement Learning for Physical Dynamical Systems: An Alternative Approach πŸ—‚ Category: MACHINE LEARNING πŸ•’ Date: 2024-07-28 | ⏱️ Read time: 17 min read Reintroducing genetic algorithms and comparing to neural networks

πŸ“Œ Can AI Agents Do Your Day-to-Day Tasks on Apps? πŸ—‚ Category: LARGE LANGUAGE MODELS πŸ•’ Date: 2024-07-28 | ⏱️ Read time: 9 m
πŸ“Œ Can AI Agents Do Your Day-to-Day Tasks on Apps? πŸ—‚ Category: LARGE LANGUAGE MODELS πŸ•’ Date: 2024-07-28 | ⏱️ Read time: 9 min read Benchmarking coding agents in a world of apps and people

πŸ“Œ How to Create an LLM-Powered app to Convert Text to Presentation Slides: GenSlide – A Step-by-step… πŸ—‚ Category: MACHINE L
πŸ“Œ How to Create an LLM-Powered app to Convert Text to Presentation Slides: GenSlide – A Step-by-step… πŸ—‚ Category: MACHINE LEARNING πŸ•’ Date: 2024-07-29 | ⏱️ Read time: 9 min read Create a simple yet powerful application that uses LLMs to convert your written content to…

πŸ“Œ Does Data-Driven Storytelling Need to Be Objective? πŸ—‚ Category: DATA VISUALIZATION πŸ•’ Date: 2024-07-29 | ⏱️ Read time: 14
πŸ“Œ Does Data-Driven Storytelling Need to Be Objective? πŸ—‚ Category: DATA VISUALIZATION πŸ•’ Date: 2024-07-29 | ⏱️ Read time: 14 min read Striking the balance between efficiency and engagement of your data-driven stories

πŸ“Œ Was Michael Scott the World’s Best Boss? πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-07-29 | ⏱️ Read time: 17 min read Sentime
πŸ“Œ Was Michael Scott the World’s Best Boss? πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-07-29 | ⏱️ Read time: 17 min read Sentiment analysis of β€˜The Office’ TV series using SchrutePy, NLTK and Hugging Face Transformers

πŸ“Œ A Simple Regularization for Your GANs πŸ—‚ Category: MACHINE LEARNING πŸ•’ Date: 2024-07-29 | ⏱️ Read time: 17 min read In 201
πŸ“Œ A Simple Regularization for Your GANs πŸ—‚ Category: MACHINE LEARNING πŸ•’ Date: 2024-07-29 | ⏱️ Read time: 17 min read In 2018, I had the privilege of orally presenting my paper at the AAAI conference.…

πŸ“Œ You Didn’t Conduct an A/B Test. You Can Still Simulate One Retrospectively. πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-07-29
πŸ“Œ You Didn’t Conduct an A/B Test. You Can Still Simulate One Retrospectively. πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-07-29 | ⏱️ Read time: 17 min read Modeling a synthetic (but high quality) control group as a baseline to infer whether the…

πŸ“Œ Maximize Savings on Your Unused Fabric Capacities πŸ—‚ Category: DATA ENGINEERING πŸ•’ Date: 2024-07-29 | ⏱️ Read time: 9 min
πŸ“Œ Maximize Savings on Your Unused Fabric Capacities πŸ—‚ Category: DATA ENGINEERING πŸ•’ Date: 2024-07-29 | ⏱️ Read time: 9 min read Automate your Microsoft Fabric capacity state with Azure Logic Apps Disclaimer: This post will not…

πŸ“Œ Fine-Tune Llama 3.1 Ultra-Efficiently with Unsloth πŸ—‚ Category: LARGE LANGUAGE MODELS πŸ•’ Date: 2024-07-29 | ⏱️ Read time:
πŸ“Œ Fine-Tune Llama 3.1 Ultra-Efficiently with Unsloth πŸ—‚ Category: LARGE LANGUAGE MODELS πŸ•’ Date: 2024-07-29 | ⏱️ Read time: 14 min read A beginner’s guide to state-of-the-art supervised fine-tuning

πŸ“Œ Isochrones in Python πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-07-29 | ⏱️ Read time: 4 min read Highlighting walkability are
πŸ“Œ Isochrones in Python πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-07-29 | ⏱️ Read time: 4 min read Highlighting walkability areas in Python

πŸ“Œ Python Set Is Way Faster Than List, True Or False? πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-07-29 | ⏱️ Read time: 6 min rea
πŸ“Œ Python Set Is Way Faster Than List, True Or False? πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-07-29 | ⏱️ Read time: 6 min read Comprehensive performance comparison and discussion around data structure

πŸ“Œ Hands on Career Path Modelling Using Markov Chain, with Python πŸ—‚ Category: CAREER ADVICE πŸ•’ Date: 2024-07-29 | ⏱️ Read ti
πŸ“Œ Hands on Career Path Modelling Using Markov Chain, with Python πŸ—‚ Category: CAREER ADVICE πŸ•’ Date: 2024-07-29 | ⏱️ Read time: 14 min read This is how I used basic probability to simulate career development

πŸ“Œ Navigating Data Science: B2C vs. B2B Analytics πŸ—‚ Category: BUSINESS πŸ•’ Date: 2024-07-29 | ⏱️ Read time: 12 min read How c
πŸ“Œ Navigating Data Science: B2C vs. B2B Analytics πŸ—‚ Category: BUSINESS πŸ•’ Date: 2024-07-29 | ⏱️ Read time: 12 min read How customer types shape data science roles and methodologies

Missed the last big airdrop? Don’t repeat it. Padma turns grinding into a clear loop: finish daily quests, unlock upgrades an
Missed the last big airdrop? Don’t repeat it. Padma turns grinding into a clear loop: finish daily quests, unlock upgrades and artifacts drops, and convert progress into PAD tokens. Start early this season to grab higher multipliers and leaderboard rewards. Start now! #ad InsideAds

πŸ“Œ Stable and fast randomization using hash spaces πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-07-29 | ⏱️ Read time: 8 min read G
πŸ“Œ Stable and fast randomization using hash spaces πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-07-29 | ⏱️ Read time: 8 min read Generate consistent assignments on the fly across different implementation environments

πŸ“Œ Visualizing 3D Spatial Data With Pydeck πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-07-29 | ⏱️ Read time: 4 min read How to cr
πŸ“Œ Visualizing 3D Spatial Data With Pydeck πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-07-29 | ⏱️ Read time: 4 min read How to create building model maps in Python

πŸ“Œ How to Stand Out in Your Data Scientist Interview πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-07-29 | ⏱️ Read time: 9 min read
πŸ“Œ How to Stand Out in Your Data Scientist Interview πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-07-29 | ⏱️ Read time: 9 min read A tip from my experience hiring Data Scientists, which even seasoned professionals aren’t aware of

πŸ“Œ Deploying dbt Projects at Scale on Google Cloud πŸ—‚ Category: DATA ENGINEERING πŸ•’ Date: 2024-07-29 | ⏱️ Read time: 13 min r
πŸ“Œ Deploying dbt Projects at Scale on Google Cloud πŸ—‚ Category: DATA ENGINEERING πŸ•’ Date: 2024-07-29 | ⏱️ Read time: 13 min read Containerising and running dbt projects with Artifact Registry, Cloud Composer, GitHub Actions and dbt-airflow

πŸ“Œ A Practical Guide to Contrastive Learning πŸ—‚ Category: DEEP LEARNING πŸ•’ Date: 2024-07-30 | ⏱️ Read time: 10 min read How t
πŸ“Œ A Practical Guide to Contrastive Learning πŸ—‚ Category: DEEP LEARNING πŸ•’ Date: 2024-07-30 | ⏱️ Read time: 10 min read How to build your very first SimSiam model with FashionMNIST

πŸ“Œ Data Warehouse, Redefined πŸ—‚ Category: DATA ENGINEERING πŸ•’ Date: 2024-07-30 | ⏱️ Read time: 9 min read Rethinking data war
πŸ“Œ Data Warehouse, Redefined πŸ—‚ Category: DATA ENGINEERING πŸ•’ Date: 2024-07-30 | ⏱️ Read time: 9 min read Rethinking data warehousing: Why redefinition is necessary even beyond Modern Data Warehouse (MDW) and Lakehouse…