Machine Learning

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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 Syria232 Technologies & Applications3 406...

📈 Analytical overview of Telegram channel Machine Learning

Channel Machine Learning (@machinelearning9) in the English language segment is an active participant. Currently, the community unites 40 040 subscribers, ranking 3 406 in the Technologies & Applications category and 232 in the Syria region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 40 040 subscribers.

According to the latest data from 22 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 372 over the last 30 days and by 2 over the last 24 hours, overall reach remains high.

Verification status: Not verified
Engagement rate (ER): The average audience engagement rate is 1.94%. Within the first 24 hours after publication, content typically collects 1.16% reactions from the total number of subscribers.
Post reach: On average, each post receives 775 views. Within the first day, a publication typically gains 466 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 23 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.

40 040

Subscribers

+224 hours

+237 days

+37230 days

775

Post views

~ 46624 hours

~ 62048 hours

1.94%

Engagement rate

~ 3

Posts per day

Ads index

beta

Posts Archive

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📌 A Career in Data Is Not Always a Straight Line, and That’s Okay 🗂 Category: AUTHOR SPOTLIGHTS 🕒 Date: 2026-04-27 | ⏱️ Read time: 9 min read Sabrine Bendimerad on why flexibility is a crucial data science skill, the risks of outsourcing… #DataScience #AI #Python

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📌 Comparing Explicit Measures to Calculation Groups in Tabular Models 🗂 Category: DATA MODELING 🕒 Date: 2026-04-27 | ⏱️ Read time: 6 min read With the advent of UDFs and their combination with calculation groups, I see a lot… #DataScience #AI #Python

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📌 How Spreadsheets Quietly Cost Supply Chains Millions 🗂 Category: PRODUCT MANAGEMENT 🕒 Date: 2026-04-27 | ⏱️ Read time: 14 min read A simulation of how a single forecast change moves through five planning teams, and why… #DataScience #AI #Python

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CVE | Cyber Vulnerabilities Exchange Group dedicated to sharing and discussing CVEs, zero-days, critical vulnerabilities, exploits, PoCs, and technical analyses of offensive and defensive security. What you'll find here: • Newly disclosed CVEs • Public and private exploits • Technical analysis and bypasses • Offensive/defensive security • Penetration testing and red team discussions Technical, direct, and straightforward content. Channel=> https://t.me/cve0day Think. Break. Secure.

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📌 I Reduced My Pandas Runtime by 95% — Here’s What I Was Doing Wrong 🗂 Category: PROGRAMMING 🕒 Date: 2026-04-26 | ⏱️ Read time: 18 min read Most slow Pandas code “works”, until it doesn’t. Learn how to spot hidden bottlenecks, avoid… #DataScience #AI #Python

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📌 Bytes Speak All Languages: Cross-Script Name Retrieval via Contrastive Learning 🗂 Category: DEEP LEARNING 🕒 Date: 2026-04-26 | ⏱️ Read time: 12 min read Why learn 8 scripts when you can learn 256 bytes? #DataScience #AI #Python

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Repost from Machine Learning with Python

GitHub repositories to enhance your Python proficiency: - Web development with Django — https://github.com/django/django - Data Science tools — https://github.com/rasbt/python-machine-learning-book - Algorithmic challenges — https://github.com/TheAlgorithms/Python - Machine learning recipes — https://github.com/ageron/handson-ml2 - Testing best practices — https://github.com/pytest-dev/pytest - Automation scripts — https://github.com/soimort/you-get - Advanced Python concepts — https://github.com/faif/python-patterns Bookmark and share https://t.me/CodeProgrammer 🌟

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Repost from Machine Learning with Python

Follow the Machine Learning with Python channel on WhatsApp: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A

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📌 The Essential Guide to Effectively Summarizing Massive Documents, Part 2 🗂 Category: LLM APPLICATIONS 🕒 Date: 2026-04-25 | ⏱️ Read time: 18 min read We have the document clusters, and it’s time to unlock their true potential! Let’s explore… #DataScience #AI #Python

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📌 Causal Inference Is Different in Business 🗂 Category: DATA SCIENCE 🕒 Date: 2026-04-25 | ⏱️ Read time: 12 min read How does decision-gravity dictate this gap? #DataScience #AI #Python

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Headline: USA vs. IRAN: The Real Story Three US aircraft carriers are now in the Middle East. Diplomacy is at a breaking point in Islamabad. Are we on the verge of an "everlasting agreement" or total escalation? Alex Barnicoat News provides the critical breakdown of the 2026 conflict: Military Analysis: Deep dives into US weaponry and Iranian naval tactics. Geopolitical Impact: How the blockade is reshaping global trade. Daily Video News: Quick, hard-hitting updates on "Actually Important News." Stay ahead of the curve: https://inside.ad/+RZg9Rk #ad 📢 InsideAd

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📌 How to Select Variables Robustly in a Scoring Model 🗂 Category: DATA SCIENCE 🕒 Date: 2026-04-24 | ⏱️ Read time: 7 min read More variables don’t make a better scoring model. Stable variables do. Here’s how to find them. #DataScience #AI #Python

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📌 How to Improve Claude Code Performance with Automated Testing 🗂 Category: AGENTIC AI 🕒 Date: 2026-04-24 | ⏱️ Read time: 10 min read Learn how to get the most out of Claude Code #DataScience #AI #Python

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📌 I Built an AI Pipeline for Kindle Highlights 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2026-04-24 | ⏱️ Read time: 12 min read A local, zero-cost project that cleans, structures, and summarizes your reading automatically #DataScience #AI #Python

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📌 Introduction to Approximate Solution Methods for Reinforcement Learning 🗂 Category: MACHINE LEARNING 🕒 Date: 2026-04-24 | ⏱️ Read time: 9 min read Learn about function approximation and the different choices for approximation functions #DataScience #AI #Python