Machine Learning with Python
68.6K subscribers
1.57K photos
136 videos
200 files
1.32K links
Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers.

Admin: @HusseinSheikho || @Hussein_Sheikho
Download Telegram
🎓 Stanford has released a new course: “Transformers & Large Language Models”

The authors are the Amidi brothers, and three free lectures are already available on YouTube. This is probably one of the most systematic introductory courses on modern LLMs.

Course content:

• Transformers: tokenization, embeddings, attention, architecture
• #LLM basics: Mixture of Experts, decoding types
• Training and fine-tuning: SFT, RL, LoRA
• Model evaluation: LLM/VLM-as-a-judge, best practices
• Tricks: RoPE, attention approximations, quantization
• Reasoning: scaling during training and inference
• Agentic approaches: #RAG, tool calling

If you are already familiar with this topic — it’s a great opportunity to refresh your knowledge and try implementing some techniques from scratch.

https://cme295.stanford.edu/syllabus/

https://t.iss.one/CodeProgrammer 🌟
Please open Telegram to view this post
VIEW IN TELEGRAM
❤14
🤖🧠 Mastering Large Language Models: Top #1 Complete Guide to Maxime Labonne’s LLM Course

🗓️ 22 Oct 2025
📚 AI News & Trends

In the rapidly evolving landscape of artificial intelligence, large language models (LLMs) have become the foundation of modern AI innovation powering tools like ChatGPT, Claude, Gemini and countless enterprise AI applications. However, building, fine-tuning and deploying these models require deep technical understanding and hands-on expertise. To bridge this knowledge gap, Maxime Labonne, a leading AI ...

#LLM #ArtificialIntelligence #MachineLearning #DeepLearning #AIEngineering #LargeLanguageModels
❤4🎉1