Jupyter Notebooks can be stored and version controlled in GitLab for what purpose?

Jupyter Notebooks are primarily used for data science applications, where they facilitate data analysis, visualization, and interactive programming. By storing and version controlling Jupyter Notebooks in GitLab, data scientists can track changes made to their analyses, collaborate with others, and maintain a history of their work. This capability is especially beneficial in data science, where reproducibility and transparency are crucial for validating results and methodologies.

In contrast, while web development projects may use various tools and technologies, they do not specifically benefit from Jupyter Notebooks. Container orchestration deals with the deployment and management of containerized applications and is unrelated to the functionalities that Jupyter Notebooks provide. Similarly, version tracking of large media files is typically managed through other means, as Git is often not suitable for handling large binary files efficiently. Thus, the primary purpose of storing and version controlling Jupyter Notebooks in GitLab aligns well with data science use cases.