Machine Learning
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Real Machine Learning β€” 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 new collection of free courses has been added:

πŸ”— 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. πŸ“š

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:

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

The idea was appreciated. πŸ‘

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. πŸ—ΊοΈ

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

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πŸš€ Level up your AI & Data Science skills with HelloEncyclo β€” a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
βœ… 13 courses live + 40+ coming soon
🎯 One access, lifetime updates
πŸ”‘ Use code: PRESALE-BOOK-WAVE-2GFG
πŸ‘‰ https://helloencyclo.com/?ref=HUSSEINSHEIKHO
❀3
If you already have 200 open tabs with courses, articles, and GitHub repositories on ML, this repository might save the situation a bit. πŸ˜…

Awesome Machine Learning Resources is a huge collection of sub-collections on machine learning, deep learning, and AI. πŸ€–

Instead of endless Google searches, everything is organized into categories:

β€’ fundamentals of machine learning
β€’ neural networks and modern architectures
β€’ tasks and application areas
β€’ datasets
β€’ libraries and tools
β€’ fairness and AI ethics
β€’ production ML and MLOps

Each link has a short description, so you can quickly understand whether it's worth opening it or skipping it. πŸ“

I particularly liked that the authors mark abandoned collections with an icon if they haven't been updated in over a year. ⚠️

https://github.com/ZhiningLiu1998/awesome-machine-learning-resources

#MachineLearning #DeepLearning #AI #MLOps #DataScience #TechResources

✨ Join Best TG Channels https://xn--r1a.website/addlist/0f6vfFbEMdAwODBk

⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A

πŸš€ Level up your AI & Data Science skills with HelloEncyclo β€” a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
βœ… 13 courses live + 40+ coming soon
🎯 One access, lifetime updates
πŸ”‘ Use code: PRESALE-BOOK-WAVE-2GFG
πŸ‘‰ https://helloencyclo.com/?ref=HUSSEINSHEIKHO
❀2
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Someone spent several months manually writing a 200-page guide on mathematics and the basics of machine learning. πŸ“˜

No marketing fluff or endless links between articles. Just an attempt to gather all the most important things in one place. 🎯

Inside:

β€’ neural networks: backpropagation, SGD, Adam, BatchNorm; βš™οΈ
β€’ classic ML: SVM, Gradient Boosting, K-Means, PCA; πŸ“Š
β€’ hardware for AI: Tensor Cores, Systolic Arrays, CUDA; πŸ–₯️
β€’ transformers: Multi-Head Attention, KV Cache, LoRA; 🧠
β€’ computer vision: ViT, CNN, MAE, IoU, NMS, VLM; πŸ‘οΈ
β€’ agent systems: ReAct, memory, orchestration, OpenClaw. πŸ€–

The author describes it as the material he would have wanted to receive himself several years ago. πŸ•°οΈ

And yes, the entire guide is distributed free of charge. πŸ†“

https://www.arjunvirk.com/writing/ml-guide

#MachineLearning #AI #DeepLearning #DataScience #NeuralNetworks #Tech

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⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A

πŸš€ Level up your AI & Data Science skills with HelloEncyclo β€” a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
βœ… 13 courses live + 40+ coming soon
🎯 One access, lifetime updates
πŸ”‘ Use code: PRESALE-BOOK-WAVE-2GFG
πŸ‘‰ https://helloencyclo.com/?ref=HUSSEINSHEIKHO
❀3
πŸ”– A large collection of AI projects for practice

We found a repository that will help you move from theory to real development of AI applications.

Inside are dozens of ready-made projects: AI analytics, RAG systems, OCR applications, code review agents, travel assistants, and much more.

⛓️ Link to GitHub: https://github.com/Sumanth077/Hands-On-AI-Engineering

#AI #MachineLearning #Python #DataScience #OpenSource #Tech

✨ Join Best TG Channels https://xn--r1a.website/addlist/0f6vfFbEMdAwODBk

⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A

πŸš€ Level up your AI & Data Science skills with HelloEncyclo β€” a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
βœ… 13 courses live + 40+ coming soon
🎯 One access, lifetime updates
πŸ”‘ Use code: PRESALE-BOOK-WAVE-2GFG
πŸ‘‰ https://helloencyclo.com/?ref=HUSSEINSHEIKHO
❀5