feed-forward neural networks explore the preceding optimization techniquesand othersin greater detail adagrad and adadelta are popular and highly recommended choices practical implementation with pytorch so farwe have provided brief overview of the essential topics of feedforward neural network we will now implement simple network using pytorch the idea of introducing all the building blocks necessary for the first network makes the process of lazy learning (learning constructs as and when necessaryin pytorch more effective listing - imports the essential python packages for the exercise listing - importing the necessary python packages #import required libraries import torch as tch import torch nn as nn import numpy as np from sklearn datasets import make_blobs from matplotlib import pyplot we will need torch and its neural network modulealong with numpymatplotlib (for visualizationand sklearn (for creating dummy datasetsalthough there are million ways to create dummy datasetswe will leverage simple function provided within sklearn note in this bookwe are using couple of popular python packages relevant to machine learning most of these packages come installed with an anaconda distribution additional packagesif requiredwill be specifically called out