deep learning neural network basics implementation using tensorflow

import the modules then read the data set then Inspect the shape of training and testing then define the model then Define the weights and biases for each layer of the model then Initialize all the variables then Call the defined model then Define the cost function and optimizer then Calculate the cost and accuracy for each epoch then print the final accuracy then print the final mean square error then print accuracy run