Diffusion Based Image Generation with Diffuser (Full Course) - Latent Diffusion Models Tutorial | The Backbone of Stable Diffusion Explained

#stablediffusion #aiart #python #generativeai #diffusion #pytorch I am Dr. Balyogi Mohan Dash, and I welcome you to Intelligent Machines! Explore the core of Latent Diffusion Models (LDMs) — the foundation behind Stable Diffusion, Flux, and modern text-to-image AI systems. In this video, I explain how diffusion in latent space enables high-resolution image generation with minimal GPU cost. Learn about VAE encoding, UNet architecture, and scaling factors, and see why LDMs revolutionized generative AI. Perfect for anyone studying AI, diffusion models, or deep learning. All code used in this video is available here: https://github.com/mohan696matlab/Diffusion_Gen_AI_Course Subscribe to the channel to follow this complete course and master diffusion models from theory to practical implementation. 🔗Links🔗 LinkedIn: https://www.linkedin.com/in/balyogi-mohan-dash/ GitHub: https://github.com/mohan696matlab Google Scholar: https://scholar.google.com/citations?user=jzcIElIAAAAJ&hl=en WhatsApp inquiries are currently closed. Please reach out via email for any questions: [email protected] 00:00 - Introduction to Latent Diffusion Models 00:30 - The Problem with Basic Diffusion Models 01:30 - Why We Need Latent Space Diffusion 02:00 - Latent Diffusion Model Architecture Explained 03:30 - Implementation: UNet and VAE in Action 04:30 - Encoding, Scaling, and Latent Visualization 06:00 - Decoding and Image Reconstruction 06:45 - Next Steps: Text-Conditioned Latent Diffusion