Visualizing your training data is the foundation of every successful deep learning project. It’s important to both identify potential flaws in the ground truth labels, and to look for insights that will guide your choice of model architecture.
Visualizing your training data is the foundation of every successful deep learning project. It’s important to both identify potential flaws in the ground truth labels, and to look for insights that will guide your choice of model architecture.