Machine Learning – Telegram
Machine Learning
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Machine learning insights, practical tutorials, and clear explanations for beginners and aspiring data scientists. Follow the channel for models, algorithms, coding guides, and real-world ML applications.

Admin: @HusseinSheikho || @Hussein_Sheikho
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Data Science Roadmap.pdf
15.5 MB
🏷 Comprehensive Data Science Roadmap Notes

This roadmap is exactly the secret recipe you need to get out of confusion and know how to step-by-step prepare yourself for the job market.

🕡 From mastering Python and SQL to cleaning data and working with cloud tools, which are prerequisites for any project.

🕑 How to extract real analysis reports and strategies from raw data using statistics and visualization tools.

🕗 You will learn everything from machine learning and advanced algorithms to precise model evaluation.

🕙 Get familiar with neural networks, generative artificial intelligence, and language models to have a voice in today's modern world.

🕧 How to build real projects and portfolios that are exactly what hiring managers and big companies are looking for.

🌐 #DataScience #DataScience #pytorch #python #Roadmap

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📌 The Reality of Vibe Coding: AI Agents and the Security Debt Crisis

🗂 Category: LLM APPLICATIONS

🕒 Date: 2026-02-22 | ⏱️ Read time: 6 min read

Why optimizing for speed over safety is leaving applications vulnerable, and how to fix it.

#DataScience #AI #Python
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📌 Is the AI and Data Job Market Dead?

🗂 Category: DATA SCIENCE

🕒 Date: 2026-02-23 | ⏱️ Read time: 8 min read

What you should be doing in the current job market

#DataScience #AI #Python
📌 PySpark for Pandas Users

🗂 Category: DATA ENGINEERING

🕒 Date: 2026-02-23 | ⏱️ Read time: 16 min read

Common Pandas operations and their equivalents in PySpark

#DataScience #AI #Python
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📌 AI in Multiple GPUs: Gradient Accumulation & Data Parallelism

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2026-02-23 | ⏱️ Read time: 9 min read

Learn and implement gradient accum and data parallelism from scratch in PyTorch

#DataScience #AI #Python
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📌 Build Effective Internal Tooling with Claude Code

🗂 Category: LLM APPLICATIONS

🕒 Date: 2026-02-23 | ⏱️ Read time: 10 min read

Use Claude Code to quickly build completely personalized applications

#DataScience #AI #Python
📌 Optimizing Deep Learning Models with SAM

🗂 Category: DEEP LEARNING

🕒 Date: 2026-02-24 | ⏱️ Read time: 16 min read

A deep dive into the Sharpness-Aware-Minimization (SAM) algorithm and how it improves the generalizability of…

#DataScience #AI #Python
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📌 AI Bots Formed a Cartel. No One Told Them To.

🗂 Category: AGENTIC AI

🕒 Date: 2026-02-24 | ⏱️ Read time: 11 min read

Inside the research that shows algorithmic price-fixing isn’t a bug in the code. It’s a…

#DataScience #AI #Python
📌 Optimizing Token Generation in PyTorch Decoder Models

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2026-02-24 | ⏱️ Read time: 17 min read

Hiding host-device synchronization via CUDA stream interleaving

#DataScience #AI #Python
Make AI write like a real human (and pass every checker) 100% free, No login, Unlimited use, Multi-language support Trusted by 50k+ users already. Your turn! 👉 https://unaimytext.com
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Machine Learning pinned «Make AI write like a real human (and pass every checker) 100% free, No login, Unlimited use, Multi-language support Trusted by 50k+ users already. Your turn! 👉 https://unaimytext.com»
📌 Decisioning at the Edge: Policy Matching at Scale

🗂 Category: DATA SCIENCE

🕒 Date: 2026-02-24 | ⏱️ Read time: 13 min read

Policy-to-Agency Optimization with PuLP

#DataScience #AI #Python
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📌 Aliasing in Audio, Easily Explained: From Wagon Wheels to Waveforms

🗂 Category: MACHINE LEARNING

🕒 Date: 2026-02-25 | ⏱️ Read time: 21 min read

Understanding the foundational distortion of digital audio from first principles, with worked examples and visual…

#DataScience #AI #Python
📌 How to Define the Modeling Scope of an Internal Credit Risk Model

🗂 Category: DATA SCIENCE

🕒 Date: 2026-02-25 | ⏱️ Read time: 9 min read

Dataset construction for Internal Ratings-Based (IRB) Probability of Default (PD) models

#DataScience #AI #Python