Question

An over-trained DeepRacer model won't perform well in the real world because it can't handle even minor variations between the simulated track and the real environment. An over-trained DeepRacer model won't perform well in the real world because it can't handle even minor variations between the simulated track and the real environment. True False

Name: an over trained deepracer model wont perform well in the real world because it cant handle even minor variations between the simulated track and the real environment an over trained deeprace 72802
Uploaded: 2021-11-14T14:38:45-08:00
Duration: 2 min 17 s
Channel: Christopher Dzorkpata
Description: an over trained deepracer model wont perform well in the real world because it cant handle even minor variations between the simulated track and the real environment an over trained deeprace 72802

          An over-trained DeepRacer model won't perform well in the real world because it can't handle even minor variations between the simulated track and the real environment.
An over-trained DeepRacer model won't perform well in the real world because it can't handle even minor variations between the simulated track and the real environment.
True
False

Added by Philip B.

Computer Science and Information Technology

Trishna Knowledge Systems 2018 Edition

Instant Answer

Solved by Expert Christopher Dzorkpata

11/14/2021

Step 1

Over-training, also known as overfitting, occurs when a model learns the training data too well, including noise and outliers. This results in a model that performs well on the training data but poorly on unseen data, such as the real world. Show more…

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An over-trained DeepRacer model won't perform well in the real world because it can't handle even minor variations between the simulated track and the real environment. An over-trained DeepRacer model won't perform well in the real world because it can't handle even minor variations between the simulated track and the real environment. True False