Deep Learning with PyTorch

5 The mechanics of learning

This chapter covers

• Understanding how algorithms can learn from data
• Reframing learning as parameter estimation, using differentiation and gradient descent
• Walking through a simple learning algorithm
• How PyTorch supports learning with autograd

With the blooming of machine learning that has occurred over the last decade, the notion of machines that learn from experience has become a mainstream theme in both technical and journalistic circles. Now, how is it exactly that a machine learns? What are the mechanics of this process--or, in words, what is the algorithm behind it? From the point of view of an observer, a learning algorithm is presented with input data that is paired with desired outputs. Once learning has ...