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Course Outline

Introduction to Mistral Multimodal Models

  • Overview of Mistral Medium and its multimodal features
  • OCR and document models: applications and use cases
  • Integration with open-source ecosystems

OCR and Vision Pipelines

  • OCR fundamentals using Mistral models
  • Image and scanned document preprocessing
  • Extraction of structured text from visual inputs

Document Understanding

  • Architecture of NLP pipelines for document processing
  • Entity recognition, summarization, and classification tasks
  • Cross-modal connection between text and vision data

Search and Knowledge Applications

  • Vision-text search system design
  • Semantic search implementation using OCR outputs
  • Management of enterprise document repositories

Assistive and Interactive Applications

  • UI design principles for multimodal assistants
  • Accessibility solutions (e.g., vision-to-text conversion)
  • Practical productivity tool development

Performance and Optimization

  • Scalability strategies for multimodal pipelines
  • Inference performance tuning and optimization
  • Assessing the balance between accuracy and efficiency

Case Studies and Future Directions

  • Real-world industry applications of multimodal AI
  • Evolving research trends in OCR and document AI
  • Responsible AI practices in vision-text tasks

Summary and Next Steps

Requirements

  • A solid grasp of natural language processing concepts
  • Proficiency with Python and common ML frameworks
  • Basic knowledge of computer vision principles

Target Audience

  • Product teams
  • ML researchers
  • Applied ML engineers
 14 Hours

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Price per participant

Provisional Upcoming Courses (Require 5+ participants)

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