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Evaluate the model with the testing data, report the accuracy; compute and print the predicted decision for every input of the testing data (approved or denied) alongside with the real labels.
Evaluate the model with the testing data, report the accuracy; compute and print the predicted decision for every input of the testing data (approved or denied) alongside with the real labels.
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Posted on:Apr 22,2023
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Implement a Neural Network using Pytorch Credit Card Approval. On one of the first lectures, a credit card approval record with multiple predictors
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Create a CNN that predicts the whether the car can safely remain on the current position (i.e., drive straight) without crashing into non-drivable terrain
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Posted on:Oct 31,2022
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Task 1: Train a CNN to predict a clear road ahead 15 pointsThe python program sprites.py creates a training and test set of “minirace”
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Why is it important to split the data into separate training, validation and testing sets?
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Posted on:Oct 8,2022
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ASSIGNMENT What makes neural networks good for modeling PUFs? Why is it important to split the data into separate training, validation and
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