There are many ways to introduce and explain neural networks, most of which require learners to have a certain level of prior knowledge.

However, how to quickly understand deep learning based on neural network models within a limited time, building on the first part of the course, is a challenge.

Here, I will use the most cost-effective approach to help you deeply understand neural network models. No free lunches. We first need to take some time to build a bridge.

To build this bridge, we will introduce the concept of feature extraction in the first lecture and present the most fundamental data-driven solution, PCA.

Then, in the second lecture, we will revisit PCA from a machine learning perspective using a practical example.

I believe that once you fully understand the content of the first two lectures, you will smoothly grasp ANN models and the core concepts of deep learning.