🤖 Generative AI Foundations & Framework Notes
- Microsoft Generative AI for Beginners (
microsoft/generative-ai-for-beginners): A robust, 21-lesson structured course focusing entirely on GenAI applications. It features highly scannable lecture notes detailing the foundational differences between discriminative and generative paradigms, prompt engineering, and building agent architectures.
👉 Microsoft GenAI-for-Beginners GitHub Repository [1, 2, 3, 4] - GenAI Roadmap with Notes and Projects (
AdilShamim8/GenAI-Roadmap-with-Notes-and-Projects): A community-driven study log and notebook series tracking daily milestones in GenAI architecture. It covers LangChain component integration, multi-agent frameworks, model quantization (INT4/INT8), and Retrieval-Augmented Generation (RAG) implementation.
👉 AdilShamim8 GenAI Notes GitHub Repository [1, 2] - Generative AI with LLMs Notes (
MalayAgr/generative-ai-with-llms-notes): A dedicated collection of raw study notes compiled from high-level enterprise AI deep dives. It breaks down multi-GPU computing strategies, distributed data training configurations, and inference hyperparameters (such as temperature, top-k, and top-p settings).
👉 MalayAgr LLM Notes GitHub Repository [1]