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Course Outline
Introduction to Mistral’s Multimodal Capabilities
- Explore the features of Mistral Medium and its multimodal potential
- Examine OCR and document models along with their practical applications
- Discuss integration strategies within open-source ecosystems
Developing OCR and Vision Pipelines
- Master the fundamentals of OCR using Mistral models
- Learn techniques for preprocessing images and scanned documents
- Extract structured text from visual data
Advancing Document Understanding
- Design effective NLP pipelines for processing documents
- Implement entity recognition, summarization, and classification tasks
- Establish cross-modal connections between text and vision data
Building Search and Knowledge Applications
- Create efficient vision-text search systems
- Develop semantic search capabilities leveraging OCR outputs
- Manage enterprise-level document repositories
Creating Assistive and Interactive Solutions
- Design user interfaces for multimodal assistants
- Implement accessibility features, such as vision-to-text conversion
- Develop practical, real-world productivity tools
Optimizing Performance and Scalability
- Scale multimodal pipelines for broader deployment
- Tune inference performance for optimal results
- Analyze the trade-offs between accuracy and efficiency
Case Studies and Future Trajectories
- Review industry applications of multimodal AI
- Discuss current research trends in OCR and document AI
- Address responsible AI considerations in vision-text tasks
Conclusion and Path Forward
Requirements
- A solid grasp of natural language processing concepts
- Hands-on experience with Python and various ML frameworks
- Basic knowledge of computer vision principles
Target Audience
- Product development teams
- ML researchers
- Applied ML engineers
14 Hours