Theory of Intelligence
DEEP LEARNING•Neural Networks•Building Networks In Pytorch•4.1 Tensors & Autograd

Introduction

PyTorch's two foundations: tensors (multi-dimensional arrays that can live on a GPU) and autograd (automatic gradients for any computation).

Introduction

PyTorch is the most widely used deep-learning library in research and industry. Almost everything in it rests on two ideas:

  1. Tensors — multi-dimensional arrays of numbers, like NumPy arrays, but able to run on GPUs;
  2. Autograd — PyTorch watches every operation you do on tensors and can automatically compute gradients, which is exactly what training needs.

If NumPy is a calculator, PyTorch is a calculator that can also tell you, for every number you typed in, how much it affected the final answer.

Discuss theoretical concepts, mathematical formulas, and architectural foundations.

Supports inline code with `backticks`
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