Deep Learning with PyTorch

3 It starts with a tensor

This chapter covers

• Understanding tensors, the basic data structure in PyTorch
• Indexing and operating on tensors
• Interoperating with NumPy multidimensional arrays
• Moving computations to the GPU for speed

In the previous chapter, we took a tour of some of the many applications that deep learning enables. They invariably consisted of taking data in some form, like images or text, and producing data in another form, like labels, numbers, or more images or text. Viewed from this angle, deep learning really consists of building a system that can transform data from one representation to another. This transformation is driven by extracting commonalities from a series of examples that demonstrate the desired mapping. For ...