Introduction to Deep Learning
In the previous chapter, we understood how to use modern machine learning models to tackle time series forecasting. Now, let’s focus our attention on a subfield of machine learning that has shown a lot of promise in the last few years – deep learning. We will be trying to demystify deep learning and go into why it is popular nowadays. We will also break down deep learning into major components and learn about the workhorse behind deep learning – gradient descent.
In this chapter, we will be covering these main topics:
- What is deep learning and why now?
- Components of a deep learning system
- Representation learning
- Linear layers and activation functions
- Gradient descent
