Clean and Curate Data for ViT
Prepare Dataset for ViT
Fine-Tune ViT Models with PyTorch
Install and use ViT frameworks
Understand Visual Transformer Model architecture
Establish guidelines for obtaining RAW Data
Perform End-to-End Fine-Tuning of ViT
Deploy and Maximize ViT Model Performance
Describe patches and embeddings in ViT
Essential Skills Gained
Clean and Curate Data for ViT
Prepare Dataset for ViT
Fine-Tune ViT Models with PyTorch
Install and use ViT frameworks
Format
3 day course with lecture and hands-on labs.
Audience
Project Managers
Architects
Developers
Data Acquisition Specialists
Description
You will develop the skills to obtain and organize data for fine-tuning pre-trained Vision Transformers (ViT). Combining lectures and hands-on labs, the course covers ViT transformer-based architectures, Python programming for AI models, and deploying open-source Transformer models. You will gather, clean, label, and organize data, gaining practical experience with ViT frameworks through hands-on exercises. Advanced topics like context extension, fine-tuning, and quantization for Road Surface Image Classification are explored. The course concludes with the opportunity to earn an AI certification from Alta3 Research, ideal for Python Developers, DevSecOps Engineers, and Managers or Directors seeking practical AI applications in the enterprise.
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