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Course Outline
Introduction to Mistral Multimodal Models
- Overview of Mistral Medium and multimodal capabilities
- OCR/document models and use cases
- Integration with open-source ecosystems
OCR and Vision Pipelines
- OCR fundamentals with Mistral models
- Preprocessing images and scanned documents
- Extracting structured text from images
Document Understanding
- Designing NLP pipelines for documents
- Entity recognition, summarization, and classification
- Cross-modal linking of text and vision data
Search and Knowledge Applications
- Vision-text search systems
- Building semantic search with OCR outputs
- Enterprise document repositories
Assistive and Interactive Applications
- UI design for multimodal assistants
- Accessibility applications (e.g., vision-to-text)
- Real-world productivity tools
Performance and Optimization
- Scaling multimodal pipelines
- Inference performance tuning
- Evaluating accuracy and efficiency trade-offs
Case Studies and Future Directions
- Industry applications of multimodal AI
- Research trends in OCR and document AI
- Responsible AI considerations in vision-text tasks
Summary and Next Steps
Requirements
- An understanding of natural language processing concepts
- Experience with Python and ML frameworks
- Familiarity with computer vision basics
Audience
- Product teams
- ML researchers
- Applied ML engineers
14 Hours
