What type of labeled data pairs does a pure end-to-end autonomous driving system require for training?

End-to-end learning systems are not always a good choice, even when they can be remarkably successful with abundant data.

To train a pure end-to-end autonomous driving system, you need a large dataset of (Image, _____) pairs.

Match each end-to-end learning domain to the specific labeled input-output data pairs required to train it.

Order the causal chain explaining why a pure end-to-end autonomous driving system is difficult to train.

Why does collecting training data for a pure end-to-end autonomous driving system require specially instrumented cars?

End-to-end learning systems tend to perform well when large amounts of labeled data exist for both the input end and the output end.

When sufficient labeled input-output data is not available, you should approach end-to-end learning with great _____.

Match each data collection challenge for end-to-end autonomous driving to the consequence described in Machine Learning Yearning.

Order the reasoning steps a practitioner should follow when evaluating whether to use a pure end-to-end approach for a new problem.

Analyzing Data Requirements for End-to-End Systems

Evaluating End-to-End Learning Viability

Resource Requirements for Autonomous Data Collection