{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/a469637de0df4ed9b630ff1b6ec29762\" frameborder=\"0\" width=\"1920\" height=\"1440\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1440,"width":1920,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1440,"thumbnail_width":1920,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/a469637de0df4ed9b630ff1b6ec29762-11f8c6392811eecb.gif","duration":385.243,"title":"Feature Engineering","description":"In 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!"}