Ho Chi Minh City Saigon Tower

16th Floor, Saigon Tower, 29 Le Duan Street, Ho Chi Minh City, Vietnam
The office space in Ho Chi Minh City Saigon Tower is in a prestigious building in the heart of the central business district....

The Executive Centre - Saigon Centre Tower 1

Level 14, Tower 1, 65 Le Loi Street, Ben Nghe Ward, District 1, Ho Chi Minh City, Vietnam, 700000
Right in heart of Ho Chi Minh city, strategically located in the coveted District 1 on Le Loi Street.

Explore Our Courses

Advanced Stable Diffusion: Deep Learning for Text-to-Image Generation

 21 Hours
This instructor-led, live training in Ho Chi Minh City (online or onsite) is aimed at intermediate to advanced-level data scientists, machine learning engineers, deep learning researchers, and computer vision experts who wish to expand their knowledge and skills in deep learning for text-to-image generation. By the end of this training, participants will be able to:
  • Understand advanced deep learning architectures and techniques for text-to-image generation.
  • Implement complex models and optimizations for high-quality image synthesis.
  • Optimize performance and scalability for large datasets and complex models.
  • Tune hyperparameters for better model performance and generalization.
  • Integrate Stable Diffusion with other deep learning frameworks and tools
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Introduction to Stable Diffusion for Text-to-Image Generation

 21 Hours
This instructor-led, live training in (online or onsite) is aimed at data scientists, machine learning engineers, and computer vision researchers who wish to leverage Stable Diffusion to generate high-quality images for a variety of use cases. By the end of this training, participants will be able to:
  • Understand the principles of Stable Diffusion and how it works for image generation.
  • Build and train Stable Diffusion models for image generation tasks.
  • Apply Stable Diffusion to various image generation scenarios, such as inpainting, outpainting, and image-to-image translation.
  • Optimize the performance and stability of Stable Diffusion models.
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