‫Now, we have prepared our data for image classifier.
‫The next step is model creation.
‫There are two ways to create and train your model in keras.
‫The first one is the sequential model api and the second one is the functional api.
‫Sequential api is a straight forward and simple, whereas functional api is little bit complex, but
‫it will give you the flexibility to create some complex neural networks. Sequential
‫Api is useful to create layer by layer models such as these, where all the outputs of previous layer
‫are connected as inputs of the next layer and so on.
‫So for a simple neural network like this, sequential api is recommended.
‫But for some advanced complex structure such as this, here we are using input as an input for concat
‫layer as well.
‫So this layer have two inputs.
‫One, all of our primary input parameters and the outputs of hidden layer as well.
‫So anywhere if you want complex structure like this or you want to only use some part of your input
‫in one hidden layer and other part of input in some other hidden layer, for all such variations, you
‫can use functional api.
‫But for a straight forward, dense neural networks like this, you can use sequential api.
‫In this course first, we will use the sequential api.
‫Then we will also look at this example of functional api.