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Duration 14 hours
Course Outline
Foundations of Mistral Multimodal Models
- Introduction to Mistral Medium and its multimodal capabilities
- Exploration of OCR and document-specific models with practical use cases
- Leveraging integration within open-source ecosystems
OCR and Vision Processing Pipelines
- Core principles of OCR using Mistral models
- Techniques for preprocessing images and scanned documents
- Methods for extracting structured text from visual data
Advanced Document Understanding
- Architecting NLP pipelines specifically for document processing
- Implementing entity recognition, summarization, and classification tasks
- Linking text and vision data across modalities
Search and Knowledge Management Solutions
- Designing vision-text search systems
- Creating semantic search experiences utilizing OCR outputs
- Managing enterprise-scale document repositories
Assistive and Interactive Technologies
- User interface design for multimodal AI assistants
- Accessibility features, such as vision-to-text conversion
- Developing real-world productivity enhancements
Performance Optimization and Scaling
- Strategies for scaling multimodal pipelines
- Tuning inference performance for optimal speed
- Balancing accuracy against computational efficiency
Industry Case Studies and Future Trends
- Real-world industry applications of multimodal AI
- Emerging research trends in OCR and document intelligence
- Ethical and responsible AI practices in vision-text tasks
Conclusions and Recommended Next Steps
Requirements
- Solid grasp of Natural Language Processing (NLP) principles
- Proficiency in Python and popular machine learning frameworks
- Basic knowledge of computer vision concepts
Target Audience
- Product development teams
- Machine learning researchers
- Applied ML engineers
