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Generative AI with Diffusion Models (NV-GEN-AI-DM)

Take a deeper dive into denoising diffusion models, which are a popular choice for text-to-image pipelines

Thanks to improvements in computing power and scientific theory, generative AI is more accessible than ever before. Generative AI plays a significant role across industries due to its numerous applications, such as creative content generation, data augmentation, simulation and planning, anomaly detection, drug discovery, personalized recommendations, and more. In this course, learners will take a deeper dive into denoising diffusion models, which are a popular choice for text-to-image pipelines

GK# 847006
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What You'll Learn
  • Build a U-Net to generate images from pure noise
  • Improve the quality of generated images with the denoising diffusion process
  • Control the image output with context embeddings
  • Generate images from English text prompts using the Contrastive Language—Image Pretraining (CLIP) neural network