5 Introducing PyTorch: Tensor basics

This chapter covers

  • Introducing PyTorch and PyTorch tensors
  • Using PyTorch tensor creation methods
  • Understanding tensor operations and broadcasting
  • Exploring PyTorch tensor performance on CPUs

In the previous chapter, you started with a cleaned-up version of the DC taxi data set and applied a data-driven sampling procedure in order to identify the right fraction of the data set to allocate to a held-out, test data subset. You also analyzed the results of the sampling experiments and then launched a PySpark job to generate three separate subsets of data: training, validation, and test.

This chapter takes you on a temporary detour from the DC taxi data set to prepare you to write scalable machine learning code ...

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