Today, we made significant progress on your project. We dedicated our time to working on your project codebase and delving deeper into the concept of cross-validation.
And I also watched the videos of cross validation and I learnt the Cross-validation is a robust technique used to evaluate and validate the performance of machine learning models. It involves splitting your dataset into multiple subsets or “folds” and systematically training and testing your model on different combinations of these folds.
The day was marked by significant progress on your project, refining your code, and acquiring a deep understanding of the crucial concept of cross-validation.