Build a Neural Network With Pytorch
Implement a vanilla neural network from scratch using Pytorch.
We'll cover the following...
PyTorch basics
In the previous lessons, we looked at some Pytorch code, but this time we will take a closer look at it.
Pytorch is an open-source Python deep learning framework that enables us to build and train neural networks. Pytorch is a library that helps you perform mathematical operations between matrices in their basic form because, as you will realize, deep learning is just simple linear algebra.
The fundamental building block of a Pytorch is the tensor. A tensor is an N-dimensional array. We can have an 1d array (or a vector) x=[1,2,3,4,5]
, a 2d-array y=[[1,2],[3,4]]
, and so on.
In Pytorch, these can be defined as:
X= torch.tensor([ 1,2,3,4,5])
Y= torch.tensor([1,2],[3,4]])
From there we can define almost all mathematical operations between tensors.
Z = torch.add(X,Y)
Z = torch.matmul(X,Y)
Z = 1 / (1+torch.exp(x))
Let’s revisit the neuron’s equation: ...