Worked on the HPInc/AI-Blueprints repository to streamline data visualization workflows within Jupyter Notebook environments. Focused on the FSRCNN_DIV2K_AISTUDIO.ipynb file, the developer removed embedded image display data while retaining the underlying visualization function code. This approach reduced the overall notebook size and improved readability, making it easier for collaborators to review and maintain the codebase. The work leveraged Python and data visualization techniques to enhance the usability of the notebook without compromising its analytical capabilities. Over the course of one month, the contribution centered on optimizing feature delivery and maintaining clean, efficient documentation for future development and business use.