Build a Feed-forward-neural-network for classification using Tensorflow

###**Requested Feature**

Build a Feed-forward-neural-network, compile and fit on data and in the output, f1-score, accuracy and confusion matrix must be printed, there is a function named metrics for printing the accuracy and confusion matrix. plot accuracy and loss curve for train data and validation data
Hyperparameter tuning or scalling can be done to improve the accuracy. As the dataset is imbalanced, prefer f1 score as metric while training.
Avoid under fitting and over fitting of the model.