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Duration 14 hours
Course Outline
Fundamentals of Mistral Multimodal Models
- Overview of Mistral Medium and its multimodal features
- OCR/document models and their practical applications
- Integration within open-source ecosystems
OCR and Vision Workflows
- Core OCR concepts using Mistral models
- Processing images and scanned documents
- Retrieving structured text from visual data
Document Intelligence
- Architecting NLP pipelines for documents
- Entity extraction, summarization, and categorization
- Linking text and vision data across modalities
Search and Knowledge Systems
- Systems for vision-text search
- Creating semantic search capabilities using OCR results
- Managing enterprise document repositories
Assistive and Interactive Solutions
- Designing user interfaces for multimodal assistants
- Accessibility solutions (e.g., converting vision to text)
- Practical productivity tools
Performance and Optimization
- Scaling multimodal pipelines
- Optimizing inference performance
- Assessing the balance between accuracy and efficiency
Case Studies and Future Outlook
- Industrial applications of multimodal AI
- Research developments in OCR and document AI
- Ethical AI considerations in vision-text tasks
Conclusion and Recommendations
Requirements
- A solid grasp of natural language processing concepts
- Proficiency in Python and machine learning frameworks
- Foundational knowledge of computer vision
Target Audience
- Product teams
- ML researchers
- Applied ML engineers
