video1.0<iframe src="https://www.loom.com/embed/43e6edd4de6c453baca9476f5c14e999" frameborder="0" width="1920" height="1440" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>14401920Loomhttps://www.loom.com14401920https://cdn.loom.com/sessions/thumbnails/43e6edd4de6c453baca9476f5c14e999-499ee3579d3a2e54.gif448.6In this video, I discuss my approach to feature selection, focusing on identifying important features while managing collinearity. I utilize a two-step process involving feature importance and hierarchical clustering to optimize the feature set. I also share insights on encoding techniques and the importance of preserving certain features for model accuracy. Please take a look at the solution file for the code details, and I would appreciate your feedback on this approach.