In this chapter, we have explored linear models and applied them to the tasks of linear regression, logistic regression, and multi-class classification. We have seen how autograd calculates gradients and how PyTorch works with computational graphs. The multi-class classification model we built did a reasonable job of predicting hand-written digits; however, its performance is far from optimal. The best deep learning models are able to get near 100% accuracy on this dataset.
We will see in Chapter 4, Convolutional Networks, how adding more layers and using convolutional networks can improve performance.
