9️⃣ Repositories 🔸 Neural Networks: Zero to Hero: https://lnkd.in/gEzFebK7 🔸 Awesome-computer-vision: https://lnkd.in/g7jZNFHX 🔸 Hands-on-LLMs: https://lnkd.in/g7HcxTZz 🔸 Prompt-Engineering Guide: https://lnkd.in/gJjGbxQr 🔸 Awesome-generative-ai: https://lnkd.in/g_tmrqTi 🔸 AI Agents for Beginners: https://lnkd.in/gK8MiVfv 🔸 Advanced RAG Techniques: https://lnkd.in/g2ZHwZ3w 🔸 Gen-AI Agents: https://lnkd.in/gkMZs-Ks 🔸 Made with ML: https://lnkd.in/gER7Stdw
7️⃣ Courses 🔸 MIT 6.S191 - Intro to Deep Learning: https://lnkd.in/gs5Wqzj5 🔸 Neural Networks: Zero to Hero: https://lnkd.in/gYzeJMTc 🔸 Stanford CS336 LLMs: https://lnkd.in/gMFFjPX4 🔸 UMich Deep Learning for CV: https://lnkd.in/g_eGdiWe 🔸 Stanford CS236 - Generative AI: https://lnkd.in/gb9Tx33e 🔸 Stanford MLSys: https://lnkd.in/gP3UDqwn 🔸 Berkeley LLM Agents: https://lnkd.in/g5ytvtH7
5️⃣ Essential Books 🔸 Understanding DL (Prince): https://lnkd.in/g4xgvu_q 🔸 LLMs from Scratch (Raschka): https://lnkd.in/g2YGbnWS 🔸 The LLM Handbook (Iusztin et al): https://lnkd.in/gWUT2EXe 🔸 AI Engineering (Huyen): https://lnkd.in/gpfQSMCQ 🔸 Hands-on GenAI (Sanerviero et al): https://lnkd.in/gSRgvcKA
3️⃣ Guides 🔸 Google's Agent Whitepaper: https://lnkd.in/gFvCfbSN 🔸 Building Effective Agents by Anthropic: https://lnkd.in/gRWKANS4. 🔸 OpenAI's Practical Guide to Building Agents: https://lnkd.in/guRfXsFK
1️⃣ Newsletter 🔸 Gradient Ascent: https://lnkd.in/gZbZAeQW