Comet.ml enhances the functionality of Jupyter notebooks by providing seamless integration for tracking and visualizing machine learning model results in real time. Jupyter notebooks, widely used by data scientists for their ability to combine code, text, and multimedia, have seen significant growth, with over 2.5 million public notebooks recorded in 2018. Comet.ml offers full support for Jupyter and its extensions, such as JupyterLab and Google Colaboratory, enabling data teams to track datasets, code changes, and experimentation history, thereby improving efficiency, transparency, and reproducibility. The platform's features include instant feedback, low overhead for creating complex plots, easy collaboration, and rich visualizations that allow users to compare results across iterations. Comet.ml positions itself as an essential tool for machine learning operations, comparable to GitHub's impact on software development, and encourages users to explore its capabilities through a sample notebook and a free account.