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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 40 193 subscribers, ranking 3 365 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 40 193 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.

40 193
Subscribers
+2124 hours
+857 days
+35530 days
Posts Archive
πŸ“Œ Integrating LLM Agents with LangChain into VICA πŸ—‚ Category: πŸ•’ Date: 2024-08-20 | ⏱️ Read time: 17 min read Learn how we
πŸ“Œ Integrating LLM Agents with LangChain into VICA πŸ—‚ Category: πŸ•’ Date: 2024-08-20 | ⏱️ Read time: 17 min read Learn how we use LLM Agents to improve and customise transactions in a chatbot!

πŸ“Œ How To Get A Data Science Graduate Scheme / Internship πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-08-20 | ⏱️ Read time: 8 min
πŸ“Œ How To Get A Data Science Graduate Scheme / Internship πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-08-20 | ⏱️ Read time: 8 min read My advice for university and college students wanting to get into data science

πŸ“Œ Plotly Dash β€” A Structured Framework for a Multi-Page Dashboard πŸ—‚ Category: DATA VISUALIZATION πŸ•’ Date: 2025-10-06 | ⏱️ R
πŸ“Œ Plotly Dash β€” A Structured Framework for a Multi-Page Dashboard πŸ—‚ Category: DATA VISUALIZATION πŸ•’ Date: 2025-10-06 | ⏱️ Read time: 12 min read An easy starting point for larger and more complicated Dash dashboards

πŸ“Œ How To Build Effective Technical Guardrails for AI Applications πŸ—‚ Category: ARTIFICIAL INTELLIGENCE πŸ•’ Date: 2025-10-06 |
πŸ“Œ How To Build Effective Technical Guardrails for AI Applications πŸ—‚ Category: ARTIFICIAL INTELLIGENCE πŸ•’ Date: 2025-10-06 | ⏱️ Read time: 13 min read Exploring the most practical guardrails to implement at ground level

πŸ“Œ How I Used ChatGPT to Land My Next Data Science Role πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2025-10-06 | ⏱️ Read time: 9 min r
πŸ“Œ How I Used ChatGPT to Land My Next Data Science Role πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2025-10-06 | ⏱️ Read time: 9 min read Practical AI hacks for every stage of the job searchβ€Š β€” with real prompts and examples

Your ROI shouldn’t depend on kilowatts. Padma replaces hashrate with activity-based yield: complete tasks, mint NFTs, and con
Your ROI shouldn’t depend on kilowatts. Padma replaces hashrate with activity-based yield: complete tasks, mint NFTs, and convert progress into PAD. It’s a mining mindset with modern tools and transparent economics. Start today! #ad InsideAds

πŸ“Œ Hands-on Time Series Anomaly Detection using Autoencoders, with Python πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-08-21 | ⏱️
πŸ“Œ Hands-on Time Series Anomaly Detection using Autoencoders, with Python πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-08-21 | ⏱️ Read time: 12 min read Here’s how to use Autoencoders to detect signals with anomalies in a few lines of…

πŸ“Œ What Do Large Language Models β€œUnderstand”? πŸ—‚ Category: ARTIFICIAL INTELLIGENCE πŸ•’ Date: 2024-08-21 | ⏱️ Read time: 31 mi
πŸ“Œ What Do Large Language Models β€œUnderstand”? πŸ—‚ Category: ARTIFICIAL INTELLIGENCE πŸ•’ Date: 2024-08-21 | ⏱️ Read time: 31 min read A deep dive on the meaning of understanding and how it applies to LLMs

πŸ“Œ AWS DeepRacer : A Practical Guide to Reducing The Sim2Real Gap – Part 1 πŸ—‚ Category: ROBOTICS πŸ•’ Date: 2024-08-21 | ⏱️ Rea
πŸ“Œ AWS DeepRacer : A Practical Guide to Reducing The Sim2Real Gap – Part 1 πŸ—‚ Category: ROBOTICS πŸ•’ Date: 2024-08-21 | ⏱️ Read time: 10 min read In this guide (which also happens to be my first Medium article), I will share…

πŸ“Œ 3 AI Use Cases (That Are Not a Chatbot) πŸ—‚ Category: MACHINE LEARNING πŸ•’ Date: 2024-08-21 | ⏱️ Read time: 7 min read Featu
πŸ“Œ 3 AI Use Cases (That Are Not a Chatbot) πŸ—‚ Category: MACHINE LEARNING πŸ•’ Date: 2024-08-21 | ⏱️ Read time: 7 min read Feature engineering, structuring unstructured data, and lead scoring

πŸ“Œ Creating a RAG Chatbot with Langflow and Astra DB πŸ—‚ Category: NATURAL LANGUAGE PROCESSING πŸ•’ Date: 2024-08-21 | ⏱️ Read t
πŸ“Œ Creating a RAG Chatbot with Langflow and Astra DB πŸ—‚ Category: NATURAL LANGUAGE PROCESSING πŸ•’ Date: 2024-08-21 | ⏱️ Read time: 7 min read A walkthrough on how to create a RAG chatbot using Langflow’s intuitive interface, integrating LLMs…

πŸ“Œ Fine-Tune the Audio Spectrogram Transformer With Transformers πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-08-21 | ⏱️ Read time
πŸ“Œ Fine-Tune the Audio Spectrogram Transformer With Transformers πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-08-21 | ⏱️ Read time: 15 min read Learn how to fine-tune the Audio Spectrogram Transformer model for audio classification of your own…

πŸ“Œ Understanding the Limitations of ARIMA Forecasting πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-08-21 | ⏱️ Read time: 13 min re
πŸ“Œ Understanding the Limitations of ARIMA Forecasting πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-08-21 | ⏱️ Read time: 13 min read A comparison between the SARIMA model and the Facebook Prophet model

πŸ“Œ How to Create Well-Styled Streamlit Dataframes, Part 2: using AgGrid πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-08-21 | ⏱️ Re
πŸ“Œ How to Create Well-Styled Streamlit Dataframes, Part 2: using AgGrid πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-08-21 | ⏱️ Read time: 12 min read The pandas Styler is cool. But AgGrid is way cooler. Make your Streamlit dataframes interactive…

πŸ“Œ Leveraging Gemini-1.5-Pro-Latest for Smarter Eating πŸ—‚ Category: ARTIFICIAL INTELLIGENCE πŸ•’ Date: 2024-08-21 | ⏱️ Read tim
πŸ“Œ Leveraging Gemini-1.5-Pro-Latest for Smarter Eating πŸ—‚ Category: ARTIFICIAL INTELLIGENCE πŸ•’ Date: 2024-08-21 | ⏱️ Read time: 9 min read Learn how to use Google’s Gemini-1.5-pro-latest model to develop a generative AI app for calorie…

πŸ“Œ The Forgotten Guiding Role of Data Modelling πŸ—‚ Category: DATA ENGINEERING πŸ•’ Date: 2024-08-21 | ⏱️ Read time: 12 min read
πŸ“Œ The Forgotten Guiding Role of Data Modelling πŸ—‚ Category: DATA ENGINEERING πŸ•’ Date: 2024-08-21 | ⏱️ Read time: 12 min read Getting to the bottom of what structuring your data responsibly really means

πŸ“Œ Linear Programming: The Stock Cutting Problem πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-08-22 | ⏱️ Read time: 13 min read Pa
πŸ“Œ Linear Programming: The Stock Cutting Problem πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-08-22 | ⏱️ Read time: 13 min read Part 2 – Linear Programming Example Deep Dive

Ever wondered what your workflow could look like if you had AI working for you 24/7? Meet Padma AI – your smart Telegram assi
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πŸ“Œ Learning to Unlearn: Why Data Scientists and AI Practitioners Should Understand Machine Unlearning πŸ—‚ Category: MACHINE LE
πŸ“Œ Learning to Unlearn: Why Data Scientists and AI Practitioners Should Understand Machine Unlearning πŸ—‚ Category: MACHINE LEARNING πŸ•’ Date: 2024-08-22 | ⏱️ Read time: 24 min read Explore the intersections between privacy and AI with a guide to removing the impact of…

πŸ“Œ SQL User Defined Functions (UDFs) πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-08-22 | ⏱️ Read time: 11 min read A tutorial on
πŸ“Œ SQL User Defined Functions (UDFs) πŸ—‚ Category: DATA SCIENCE πŸ•’ Date: 2024-08-22 | ⏱️ Read time: 11 min read A tutorial on mastering SQL UDFs: categories, use cases, and difference from stored procedures