2 The mathematical building blocks of neural networks
This chapter covers
- A first example of a neural network
- Tensors and tensor operations
- How neural networks learn via backpropagation and gradient descent
Understanding deep learning requires familiarity with many simple mathematical concepts: tensors, tensor operations, differentiation, gradient descent, and so on. Our goal in this chapter will be to build up your intuition about these notions without getting overly technical. In particular, we’ll steer away from mathematical notation, which can introduce unnecessary barriers for those without any mathematics background and isn’t necessary to explain things well. The most precise, unambiguous description of a mathematical operation is ...
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