Deep LearnerΒΆ
Uses a Neural Network to solve a Supervised Learning problem.
It employs three Neural Networks:
Training Network - Used to adjust the weights and biases with the help of a user-defined optimizer to minimize the loss function given in the supervised learning problem (e.g., Mean Square Error).
Validation Network - Used to measure the improvement (in terms of loss function values) of the training network on the validation data given in the supervised learning problem.
Test Network - The result of the optimisation procedure which can be used to evaluate the neural network on a test set using the test() function.
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