Automated Model Fine-Tuning and Deployment Using AWS SageMaker: A Scalable Workflow for Image Generation
Daniel Okwu · International Journal of Emerging Trends in Computer Science and Information Technology · 2022
The rapid advancement in deep learning and machine learning (ML) has led to significant improvements in various domains, including image generation. However, the process of fine-tuning and deploying these models remains challenging due to the complexity and resource requirements. This paper presents a scalable workflow for automated model fine-tuning and deployment using AWS SageMaker, focusing on image generation tasks. We describe the architecture, methodologies, and tools used to streamline the process, ensuring efficiency and scalability. The paper also includes experimental results and a comparative analysis with traditional methods, demonstrating the effectiveness and efficiency of our proposed approach.