From the course: Building Deep Learning Applications with Keras
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Building a model using the Sequential API
From the course: Building Deep Learning Applications with Keras
Building a model using the Sequential API
- [Instructor] Now we will build the recurrent neural network model. So find the Python file here, Build the RNN Model Begin, and we will start breaking down how we build the model step by step. So we are creating an RNN. This model is designed to learn patterns from data and especially with sequences like we have. So here is what each part does. So let's create the model by saying model equals to sequential. And this line sets up our model to have layers stacked one after the other. We can think of it like building blocks. Then we will go ahead and fill in these blocks here. So let's start with the simple RNN. So for simple RNN, we will start by defining the number of neurons or processing units that we will be using. We can think of each neuron as a microprocessor calculating based on the input fed to it. Next, let's define the input_shape, and the input_shape equals to, X_strain_reshaped.shape[1], X_strain_reshaped.shape[2], and return_sequences=True. So let's recall what we have…
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