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