Deep Learning: Guidelines for model optimization and tuning

a rough outline

A neural network model is represented by a set of parameters and hyperparameters. The parameters include the weights and biases of all nodes, and the hyper-parameters include a number of levers like layers, nodes in a layer, activation functions, cost functions, learning rate, and optimizers.

Training neural model means determining the right values for these parameters and hyperparameters in such a way that it maximizes the accuracy of predictions for the use case.



We put ghosts in machines.

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