From the course: Deep Learning: Getting Started
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An ANN model
From the course: Deep Learning: Getting Started
An ANN model
Having now seen the neural network constituents and the training process, let's recap the question. What is an ANN model? What does it contain? An ANN model is represented by a set of parameters, namely the weights and biases obtained during training. When someone says the model has x parameters, they are referring to the total count of the weights and bias values in that model. A model is also represented by a set of hyperparameters. This includes the number of layers, nodes in each layer, activation functions, cost functions, optimizers, and the learning rate. Hyperparameters also include the batch size and epoch values to train the model. These values control how the model is structured and how the learning process happens. A model file typically contains a representation of these values. Models can be saved to files, shared with others, and loaded into other applications for prediction or further training. Once you have a model, what does the prediction process look like? The…
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