A new collection of free courses has been added:

🔗 https://github.com/dair-ai/ML-Course-Notes

Those studying ML through dozens of random tabs and unclosed playlists may find this repository useful for organizing their learning. 📚

Machine Learning Course Notes is an open collection of notes on machine learning, NLP, and AI, compiled around full-fledged courses, not just individual videos. 🧠

What's inside:

• Courses from the Machine Learning Specialization, MIT 6.S191, CMU Neural Nets for NLP, CS224N, CS25, and others
• A table with lectures, descriptions, videos, notes, and authors
• Links to the original lectures and accompanying notes
• WIP markers for incomplete materials
• Instructions for contributors on adding and improving notes

The idea was appreciated. 👍

Instead of another collection of hundreds of links, a course map has been created where one can systematically go through the material without getting lost after a week of studying. 🗺️

#MachineLearning #AI #DataScience #TechCommunity #LearningResources #OpenSource

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🚀 Level up your AI & Data Science skills with HelloEncyclo — a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
✅ 13 courses live + 40+ coming soon
🎯 One access, lifetime updates
🔑 Use code: PRESALE-BOOK-WAVE-2GFG
👉 https://helloencyclo.com/?ref=HUSSEINSHEIKHO

Don't want to read about AI Engineering, but actually want to build something? 🛠️

We've released a collection of 50+ practical tutorials on AI Engineering as open source. 📚

Inside, you'll find step-by-step projects on:

• AI agents and multi-agent systems 🤖
• RAG (Agentic, Vision, and Local) 🔍
• MCP agents ⚙️
• OCR applications 📄
• Voice AI agents 🎙️
• and much more ✨

Everything is free, with source code and ready-made examples. 🥩

https://github.com/Sumanth077/Hands-On-AI-Engineering

#AIEngineering #MachineLearning #OpenSource #AIProjects #TechTutorials #BuildWithAI

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🚀 Level up your AI & Data Science skills with HelloEncyclo — a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
✅ 13 courses live + 40+ coming soon
🎯 One access, lifetime updates
🔑 Use code: PRESALE-BOOK-WAVE-2GFG
👉 https://helloencyclo.com/?ref=HUSSEINSHEIKHO

I often see people say that it's impossible to enter the IT field without expensive courses.

However, there's a huge amount of high-quality materials available for free:

📚 Computer Science
https://github.com/ossu/computer-science

📚 Data Structures & Algorithms
https://github.com/jwasham/coding-interview-university

📚 System Design
https://github.com/donnemartin/system-design-primer

📚 Web Development
https://github.com/TheOdinProject/curriculum

📚 Frontend / Backend / DevOps / Cloud
https://github.com/kamranahmedse/developer-roadmap

📚 Data Engineering
https://github.com/DataTalksClub/data-engineering-zoomcamp

📚 Machine Learning & AI
https://github.com/microsoft/ML-For-Beginners

📚 MLOps
https://github.com/DataTalksClub/mlops-zoomcamp

📚 Cybersecurity
https://github.com/OWASP/CheatSheetSeries

📚 Linux
https://github.com/trimstray/the-book-of-secret-knowledge

📚 Free Programming Books
https://github.com/EbookFoundation/free-programming-books

If you have internet and a bit of free time, you can learn computer science, algorithms, system design, DevOps, clouds, security, and machine learning for free.

The problem now isn't a lack of information. The problem is regularly opening these repositories and actually working on them.

#FreeLearning #ITCareer #CodingResources #TechEducation #OpenSource #DevCommunity

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🚀 Level up your AI & Data Science skills with HelloEncyclo — a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
✅ 13 courses live + 40+ coming soon
🎯 One access, lifetime updates
🔑 Use code: PRESALE-BOOK-WAVE-2GFG
👉 https://helloencyclo.com/?ref=HUSSEINSHEIKHO

Transformers become more understandable when you can "poke" the model directly. 🧠✨

Transformer Explainer is an interactive visualization tool for studying how text-generating transformer-based models, such as GPT, work. 🔍

It helps connect the architecture with real behavior by running a live GPT-2 directly in the browser, allowing you to enter your own text and showing how the internal components work together to predict the next tokens. 🔄📝

Key features: 🌟

- Live GPT-2 in the browser - experiment without setting up a separate model server 💻
- Your own text - try your own prompts and see how the model processes them ✍️
- Internal components - observe the operations working inside the transformer 🔧
- Focus on predicting the next token - link each visual step to the model's predictions 🎯
- Local development - clone the repository, install dependencies, and run via npm for in-depth study ⚙️

It's open-source (MIT license). 📜

https://github.com/poloclub/transformer-explainer

#AI #MachineLearning #GPT #DataScience #TechTools #OpenSource

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