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Now, we have prepared our data for inmates classify it.

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The next step is model creation.

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There are two ways to create and train your model in Cadeaux.

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The first one is the sequential Märta LaPier and the second one is the functional LaPier.

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Sequential EPA is a straight forward and simple, whereas functional EPA is little bit complex, but

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it will give you the flexibility to create some complex neural networks sequential.

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EPA is useful to create layer by layer models such as these, where all the outputs of previous layer

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are connected as inputs of the next layer and so on.

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So for a simple neural network like this, sequential EPA is recommended.

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But for some advanced complex, a structure such as this, here we are using input as an input for concat

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layer as well.

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So this layer have two inputs.

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One, all of our primary input parameters and the outputs of hidden layer as well.

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So anywhere if you want complex structure like this or you want to only use some part of your input

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in one hidden layer and other part of input in some other hidden layer, for all such variations, you

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can use functional LaPier.

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But for a straight forward, dense neural networks like this, you can use sequential LaPier.

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And this goes first, we will use the sequential LaPier.

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Then we will also look at this example of functional Libya.