Deep-Learning-with-PyTorch

Telling birds
from airplanes:
Learning from images
This chapter covers
• Building a feed-forward neural network
• Loading data using Datasets and DataLoaders
• Understanding classification loss
The last chapter gave us the opportunity to dive into the inner mechanics of learning
through gradient descent, and the facilities that PyTorch offers to build models
and optimize them. We did so using a simple regression model of one input and
one output, which allowed us to have everything in plain sight but admittedly was
only borderline exciting.
In this chapter, we’ll keep moving ahead with building our neural network foundations.
This time, we’ll turn our attention to images. Image recognition is arguably
the task that made the world realize the potential of deep learning.
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