Enhancement: Backtracking with logs

[msharmavikram]

There are different degrees to which we can enable Jupyter Notebook. The simplistic version is to use an MLflow-based mechanism as we did in #2. However, what I have in mind is an even more versatile solution with the assumption of an ever-changing notebook that keeps updating as the developers add a new piece of code. Here, MLSync tracks the history of these changes and creates a sort of mind map on the reasoning behind these changes and what was the impact of it. In an ideal MLsync world, we should enable tracking via git commit ids, tags marked to determine what PR id or JIRA ID corresponds to what changes and how these changes evolved over time. Personally, I see this as an exceptionally helpful tool when working with large codebases.