Lecture 3: Artificial Neural Networks and Deep Learning
In this lecture, we will learn about neural network models and deep learning models based on them. First, we will use the idea of PCA image reconstruction mentioned in the previous lecture to lay the groundwork for neural network models. After that, we will discuss the training issues of neural network models. Following the introduction to deep learning, we will provide a detailed explanation of a specific deep learning architecture, namely the convolutional neural network model.
Lecture notes:
Discussion：
Reading guidelines of textbook
For this lecture, I recommend you read sections 10.1, 10.2, 10.3, 10.6, and 10.7 of chapter 10 in the textbook, as well as the first five sections of the lab. I suggest you first read my lecture notes, and then focus on the relevant sections of the textbook based on that.
Lab session:
Laboratory: Entrance
Solutions:
Videos:
