In the realm of machine learning, the adage "Garbage In, Garbage Out" resonates. If you train your model on low-quality data you cannot expect it to function highly.
This is especially important for projects in the automotive and healthcare industries since any mistake by the model could be fatal.
Recognizing how important good data is goes beyond just technical concerns; it's a crucial strategy. It's like the base for building strong machine learning models, making sure they work well and can be trusted.