Deep Learning – What Does End to End Mean in Deep Learning Methods?

Question

I want to know what it is, and how it is any different from ensembling?

Suppose, I want to achieve high accuracy in classification and segmentation, for a specific task, if I use different networks, such as CNN, RNN, etc to achieve this, is this called an end to end model? (architecture?) or not?

Answer 1

• end-to-end = all parameters are trained jointly (vs. step-by-step)
• ensembling = several classifiers are trained independently, each classifier makes a prediction, and all predictions are combined into one using some strategy (e.g., take the most common prediction across all classifiers).