Master the art of building and optimizing cutting-edge multimodal AI systems that understand both language and vision. This course empowers you to create transformer-based models that seamlessly integrate text and image processing while leveraging transfer learning to dramatically accelerate development. You'll learn to design sophisticated architectures using PyTorch and TensorFlow, implement fusion mechanisms for cross-modal understanding, and apply advanced fine-tuning strategies that achieve peak performance on custom datasets. By mastering these techniques, you'll transform months of traditional model development into efficient workflows that deliver production-ready multimodal AI solutions. This course uniquely combines hands-on implementation with optimization strategies, preparing you to lead next-generation AI projects.
Fine-tune Multimodal Models with Transfer Learning
Fine-tune Multimodal Models with Transfer Learning
本课程是 Vision & Audio AI Systems 专项课程 的一部分
位教师：Hurix Digital
访问权限由 New York State Department of Labor 提供
您将学到什么
Multimodal architecture needs encoder-fusion-decoder pipelines balancing computational efficiency with cross-modal understanding capabilities.
Transfer learning transforms AI by enabling rapid adaptation of pre-trained knowledge to new domains with minimal data and training requirements.
Fine-tuning balances knowledge preservation and task adaptation through careful hyperparameter selection and strategic layer freezing techniques.
Production multimodal systems require systematic optimization approaches considering both model performance and computational resource constraints.
您将获得的技能
要了解的详细信息
了解顶级公司的员工如何掌握热门技能
积累特定领域的专业知识
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- 获得对主题或工具的基础理解
- 通过实践项目培养工作相关技能
- 获得可共享的职业证书
该课程共有2个模块
Learners will understand the fundamental principles of modular data pipeline design and implement basic ingestion and cleansing components using open source tools.
涵盖的内容
3个视频1篇阅读材料1个作业1个非评分实验室
Learners will implement complete modular pipeline components with transformation and loading stages, then demonstrate mastery through comprehensive assessment.
涵盖的内容
1个视频1篇阅读材料3个作业
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