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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 40 265 subscribers, ranking 3 343 in the Technologies & Applications category and 227 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 40 265 subscribers.

According to the latest data from 06 July, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 336 over the last 30 days and by -4 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 2.25%. Within the first 24 hours after publication, content typically collects 1.88% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 906 views. Within the first day, a publication typically gains 758 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.

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 07 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.

40 265
Subscribers
-424 hours
+917 days
+33630 days
Posts Archive
πŸ“Œ How I Built a Real-Time Weather Data Pipeline Using AWS-Entirely Serverless πŸ—‚ Category: DATA ENGINEERING πŸ•’ Date: 2025-01
πŸ“Œ How I Built a Real-Time Weather Data Pipeline Using AWS-Entirely Serverless πŸ—‚ Category: DATA ENGINEERING πŸ•’ Date: 2025-01-02 | ⏱️ Read time: 8 min read A practical guide to leveraging AWS Lambda, Kinesis, and DynamoDB for real-time insights

πŸ“Œ Start a New Year of Learning on the Right Foot πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2025-01-02 | ⏱️ Read time: 4 min read A
πŸ“Œ Start a New Year of Learning on the Right Foot πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2025-01-02 | ⏱️ Read time: 4 min read A special edition of must-read articles and resources to help you kick off a productive…

πŸ“Œ Data Engineering – ORM and ODM with Python πŸ—‚ Category: DATA ENGINEERING πŸ•’ Date: 2025-01-02 | ⏱️ Read time: 7 min read Ma
πŸ“Œ Data Engineering – ORM and ODM with Python πŸ—‚ Category: DATA ENGINEERING πŸ•’ Date: 2025-01-02 | ⏱️ Read time: 7 min read Manipulate database data leveraging an object-oriented programming paradigm

πŸ“Œ How to Stand Out in The Data Science Job Market πŸ—‚ Category: CAREER ADVICE πŸ•’ Date: 2025-01-02 | ⏱️ Read time: 7 min read
πŸ“Œ How to Stand Out in The Data Science Job Market πŸ—‚ Category: CAREER ADVICE πŸ•’ Date: 2025-01-02 | ⏱️ Read time: 7 min read How to have the edge in your data science application

πŸ“Œ The Fallacy of Complacent Distroless Containers πŸ—‚ Category: SECURITY AND PRIVACY πŸ•’ Date: 2025-01-02 | ⏱️ Read time: 6 mi
πŸ“Œ The Fallacy of Complacent Distroless Containers πŸ—‚ Category: SECURITY AND PRIVACY πŸ•’ Date: 2025-01-02 | ⏱️ Read time: 6 min read Making containers smaller is the most popular practice when reducing your attack surface. But how…

πŸ“Œ Demand Forecasting with Darts: A Tutorial πŸ—‚ Category: πŸ•’ Date: 2025-01-02 | ⏱️ Read time: 19 min read A hands-on tutorial
πŸ“Œ Demand Forecasting with Darts: A Tutorial πŸ—‚ Category: πŸ•’ Date: 2025-01-02 | ⏱️ Read time: 19 min read A hands-on tutorial with Python and Darts for demand forecasting, showcasing the power of TiDE…

πŸ“Œ Harnessing Polars and Geopandas to Generate Millions of Transects in Seconds πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2025-01-03
πŸ“Œ Harnessing Polars and Geopandas to Generate Millions of Transects in Seconds πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2025-01-03 | ⏱️ Read time: 11 min read Making the bears play nice

πŸ“Œ Integrating Feature Selection into the Model Estimation πŸ—‚ Category: MACHINE LEARNING πŸ•’ Date: 2025-01-03 | ⏱️ Read time:
πŸ“Œ Integrating Feature Selection into the Model Estimation πŸ—‚ Category: MACHINE LEARNING πŸ•’ Date: 2025-01-03 | ⏱️ Read time: 11 min read Combining mixture of normal regressions with in-built feature selection into powerful modeling tool

πŸ“Œ What I’m Updating in My AI Ethics Class for 2025 πŸ—‚ Category: ARTIFICIAL INTELLIGENCE πŸ•’ Date: 2025-01-03 | ⏱️ Read time:
πŸ“Œ What I’m Updating in My AI Ethics Class for 2025 πŸ—‚ Category: ARTIFICIAL INTELLIGENCE πŸ•’ Date: 2025-01-03 | ⏱️ Read time: 12 min read What happened in 2024 that is new and significant in the world of AI ethics?

πŸ“Œ Non-Technical Principles All Data Scientists Should Have πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2025-01-03 | ⏱️ Read time: 13
πŸ“Œ Non-Technical Principles All Data Scientists Should Have πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2025-01-03 | ⏱️ Read time: 13 min read Making you a better data scientist, and enhancing your career.

πŸ“Œ The Cultural Impact of AI Generated Content: Part 2 πŸ—‚ Category: πŸ•’ Date: 2025-01-03 | ⏱️ Read time: 11 min read What can
πŸ“Œ The Cultural Impact of AI Generated Content: Part 2 πŸ—‚ Category: πŸ•’ Date: 2025-01-03 | ⏱️ Read time: 11 min read What can we do about the increasingly sophisticated AI generated content in our lives?

πŸ“Œ How to Tell Among Two Regression Models with Statistical Significance πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2025-01-03 | ⏱️ R
πŸ“Œ How to Tell Among Two Regression Models with Statistical Significance πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2025-01-03 | ⏱️ Read time: 9 min read Diving into the F-test for nested models with algorithms, examples and code

πŸ“Œ Data behind the Luck, Ambition, and a Billion-Dollar Dream: Lottery πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2025-01-04 | ⏱️ Rea
πŸ“Œ Data behind the Luck, Ambition, and a Billion-Dollar Dream: Lottery πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2025-01-04 | ⏱️ Read time: 13 min read Using Seattle’s local retail store data for consumer patterns of the lottery (SQL, Python)

πŸ“Œ The Next Frontier in LLM Accuracy πŸ—‚ Category: ARTIFICIAL INTELLIGENCE πŸ•’ Date: 2025-01-04 | ⏱️ Read time: 21 min read Exp
πŸ“Œ The Next Frontier in LLM Accuracy πŸ—‚ Category: ARTIFICIAL INTELLIGENCE πŸ•’ Date: 2025-01-04 | ⏱️ Read time: 21 min read Exploring the Power of Lamini Memory Tuning

πŸ“Œ Journey to Full-Stack Data Scientist: Model Deployment πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2025-01-04 | ⏱️ Read time: 11 mi
πŸ“Œ Journey to Full-Stack Data Scientist: Model Deployment πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2025-01-04 | ⏱️ Read time: 11 min read An introduction to productionizing a machine learning model using APIs and Docker.

πŸ“Œ Awesome Plotly with Code Series (Part 7): Cropping the y-axis in Bar Charts πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2025-01-05
πŸ“Œ Awesome Plotly with Code Series (Part 7): Cropping the y-axis in Bar Charts πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2025-01-05 | ⏱️ Read time: 10 min read Is there ever a good reason for starting a bar chart above zero?

πŸ“Œ Predicting a Ball Trajectory πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2025-01-05 | ⏱️ Read time: 7 min read Polynomial Fit in Py
πŸ“Œ Predicting a Ball Trajectory πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2025-01-05 | ⏱️ Read time: 7 min read Polynomial Fit in Python with NumPy

πŸ“Œ Google’s Willow Quantum Computing Chip: A Game Changer? πŸ—‚ Category: PHYSICS πŸ•’ Date: 2025-01-06 | ⏱️ Read time: 12 min re
πŸ“Œ Google’s Willow Quantum Computing Chip: A Game Changer? πŸ—‚ Category: PHYSICS πŸ•’ Date: 2025-01-06 | ⏱️ Read time: 12 min read Suppressing Logical Errors Exponentially! For the First Time

πŸ“Œ Measuring The Execution Times of C Versus Rust πŸ—‚ Category: πŸ•’ Date: 2025-01-06 | ⏱️ Read time: 15 min read Is C is faster
πŸ“Œ Measuring The Execution Times of C Versus Rust πŸ—‚ Category: πŸ•’ Date: 2025-01-06 | ⏱️ Read time: 15 min read Is C is faster than Rust? I had always assumed the answer to that question…

πŸ“Œ Why Variable Scoping Can Make or Break Your Data Science Workflow πŸ—‚ Category: πŸ•’ Date: 2025-01-06 | ⏱️ Read time: 7 min r
πŸ“Œ Why Variable Scoping Can Make or Break Your Data Science Workflow πŸ—‚ Category: πŸ•’ Date: 2025-01-06 | ⏱️ Read time: 7 min read Let’s kick off 2025 by writing some clean code together