video1.0<iframe src="https://www.loom.com/embed/a469637de0df4ed9b630ff1b6ec29762" frameborder="0" width="1920" height="1440" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>14401920Loomhttps://www.loom.com14401920https://cdn.loom.com/sessions/thumbnails/a469637de0df4ed9b630ff1b6ec29762-11f8c6392811eecb.gif385.243In this video, I dive into the intricacies of feature engineering, sharing techniques that can streamline the process. I discuss the importance of auto feature engineering systems that can quickly extract features from raw data, which saves valuable time for data scientists. I also touch on various encoding strategies and the significance of avoiding data leakage during the process. Please take a moment to review the methods I outline, as your feedback would be greatly appreciated!