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Duration 14 hours
Course Outline
Foundations of Mistral Multimodal Models
- Overview of Mistral Medium and its multimodal capabilities
- Specifics of OCR and document models with relevant use cases
- Integration strategies within open-source ecosystems
OCR and Vision Pipeline Development
- OCR fundamentals leveraging Mistral models
- Techniques for preprocessing images and scanned documents
- Methologies for extracting structured text from visual data
Advanced Document Understanding
- Designing NLP pipelines specifically for document processing
- Implementing entity recognition, summarization, and classification
- Creating cross-modal links between text and vision data
Search and Knowledge-Driven Applications
- Architecting vision-text search systems
- Building semantic search capabilities using OCR outputs
- Managing enterprise document repositories
Assistive and Interactive Solutions
- UI design principles for multimodal assistants
- Accessibility applications, such as vision-to-text conversion
- Developing real-world productivity tools
Performance and Optimization Strategies
- Scaling multimodal pipelines for high performance
- Tuning inference performance
- Evaluating trade-offs between accuracy and efficiency
Case Studies and Future Trajectories
- Industry applications of multimodal AI
- Emerging research trends in OCR and document AI
- Responsible AI considerations in vision-text tasks
Conclusion and Next Steps
Requirements
- Foundational knowledge of natural language processing concepts
- Proficiency in Python and various ML frameworks
- Basic familiarity with computer vision principles
Target Audience
- Product teams
- ML researchers
- Applied ML engineers
