Machine Learning with Python
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Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers.

Admin: @HusseinSheikho || @Hussein_Sheikho
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📰 Awesome Open Source AI 2026 — A comprehensive collection of current open-source AI projects 🤖

This repository consolidates significant resources in a single location, including frameworks, training tools, inference utilities, RAG solutions, agents, and more. The content is organized into distinct categories to facilitate efficient navigation and resource identification for specific tasks. 📂

Repo: https://github.com/alvinreal/awesome-opensource-ai

Tags: #github #useful ✔️
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reader3 📚

When you want to connect an AI like Gemini to help you analyze books or content, copying text from a reader usually becomes a hassle. 😩💻

Especially if you want to discuss a book by chapters. Highlighting text manually and copying it disrupts the flow and feels like a waste of time. 🚫

Yesterday, Andrzej Karpati, a well-known AI expert, released a new project to the public: reader3, which solves this problem very neatly. 🎉🛠️ It's a lightweight EPUB reader that allows you to read a book together with AI. 🤖📖

Its interface is as minimalist as possible: only the necessary reading and navigation functions. 📉🧭 You can also manage your library through folders. 📁

The key feature is that it breaks an EPUB into chapters and displays the content one chapter at a time. 🔓📄

This makes it easy to copy the needed part of the book and pass it to a large model for analysis or discussion. 📋🔄 It significantly improves the reading experience when paired with AI. 🚀🧠

And it's very easy to get started - just run two commands via uv. 🛠️ As a result, it's an excellent tool for those who love reading and want to use AI as a companion for text analysis. 📚🤝🤖

📁 Language: #Python 61.0%

⭐️ Stars: 1.5k

➡️ Link to GitHub https://github.com/karpathy/reader3

#AI #Python #Reader3 #Tech #BookLovers #Github

https://xn--r1a.website/CodeProgrammer
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Found an easy way to learn math for ML: Mathematics for Machine Learning 🎓📚

This is a curated collection on GitHub, including books, research papers, video lectures, and basic materials on math for studying and reviewing the mathematical foundations of machine learning. 📖📊

It helps build a stronger knowledge base by bringing together trusted resources around topics that machine learning engineers constantly encounter: linear algebra, mathematical analysis, probability theory, statistics, information theory, matrix calculus, and deep learning mathematics. 🧮🤖

Free public repository on GitHub. 💻

https://github.com/dair-ai/Mathematics-for-ML

#MachineLearning #Mathematics #DataScience #Learning #GitHub #AI

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