Скачать или смотреть How PCA and Signal Processing Can Save Your Near IR Data!

Are you making this common mistake when analyzing Near IR data? In this video, we uncover a systematic error I discovered while running PCA on my Near IR coffee data. Before we can dive into building an accurate classification model, this error needs to be addressed. But how do you catch it, and more importantly, how do you fix it? I'll show you step-by-step how to use PCA to detect and correct systematic errors in raw data, all using Python. If you're into data science, chemistry, or spectroscopy, this video is for you. Let's dive into the science behind error correction!

Coffee Analysis EDA (part 1) :    • Видео  

0:00 intro
0:11 Recap Coffee Results
0:53 Spotting Systematic Error via PCA
1:39 Data Vis Explanation of Error
5:22 Fixing Systematic Error
6:30 Closing