November 2018
Intermediate to advanced
322 pages
7h 54m
English
As humans, we love the uncertainty that comes with predictions. For example, we always want to know what the chances are of it raining before we leave the house. However, with traditional deep learning, we only have a point prediction and no notion of uncertainty. Predictions from these networks are assumed to be accurate, which is not always the case. Ideally, we would like to know the level of confidence of predictions from neural networks before making a decision.
For example, having uncertainty in the model could have potentially avoided the following disastrous consequences:
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