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
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A free MIT guide to key computer vision concepts 📘

Link: https://visionbook.mit.edu/ 🔗

#ComputerVision #MIT #AI #MachineLearning #Tech #DataScience

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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
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Multi-agent RL is beautiful precisely at the moment when it starts to converge. 🤖

#MultiAgent #RL #ReinforcementLearning #AI #MachineLearning #DeepLearning

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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
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500 AI/ML/Computer Vision/NLP projects with code 🚀

This is a large collection of 500 ready-made projects in the field of machine learning, deep learning, computer vision, and NLP 🧠

All examples come with code, so you can not just read them, but immediately analyze and run them ⚙️

➡️ Link to GitHub:
https://github.com/ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code

#AI #MachineLearning #DeepLearning #ComputerVision #NLP #DataScience

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Don't learn ML by randomly jumping through tutorials. 🚫📚

DS-ML Bootcamp is a public repository for a Data Science and machine learning course for beginners who want a structured path from zero to practical projects. 🚀📊

It helps transition from installation and concepts to practical ML work, organizing lessons, assignments, code examples, datasets, and solutions around the main machine learning workflow. 🛠️🧠

Key features:

- End-to-end workflow - covers data collection, preprocessing, train/test split, model selection, training, evaluation, and deployment 🔄📈
- Lesson-based structure - starts with tools/setup, Data Science, ML, data fundamentals, and regression 📚🧮
- Practical materials - assignments give learners structured tasks, not just reading notes ✍️
- Code + datasets - Python examples and raw CSV datasets included for exercises 🐍📂
- Set up for repetition - the README says you can clone the repository and use Jupyter or VS Code while going through lessons 💻🔁

Free public repository on GitHub. 🆓
https://github.com/goobolabs/ds-ml-bootcamp

#MachineLearning #DataScience #Coding #Python #AI #Learning

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