What is the logic present in the layer_sizes_test_cases() function in exercise 2?
Hello Ishan Bhatt,
Welcome to the community.
In this exercise, you are trying to implement a 2-class classification neural network with a single hidden layer. There’s an input layer, followed by a hidden and an output layer. Now, to further the test cases in conjunction with the passing of the arguments X (a numpy-array (matrix) that contains features (x1, x2) & Y (a numpy-array (vector) that contains labels (red:0, blue:1), you need to have the sizes of each of the layers viz. n_x, n_h & n_y respectively.
There is a topic on the DLS FAQ Thread about how to find the code for any of the prewritten functions that are used in the assignments.