Machine Learning I

Slides¶

Lecture Video¶

The lecture video has been recorded using Zoom. Please access the video through the link here.

Passcode will be sent through Canvas announcement. You might need to use your NUS email to login.

Content¶

This week, we will cover the basic concepts of machine learning, including the types of machine learning, the difference between supervised and unsupervised learning, and the importance of data preprocessing. We will also discuss the different types of models used in machine learning, including linear regression, logistic regression, decision trees, and neural networks. Additionally, we will cover the concepts of overfitting and underfitting, as well as the importance of model evaluation and validation. In practical, we will use PyTorch to perform some basic machine learning tasks.

Learning Objectives¶

• Understand the basic concepts and types of machine learning.
• Differentiate between supervised and unsupervised learning.
• Recognize the importance of data preprocessing in machine learning.
• Identify various machine learning models such as linear regression, logistic regression, decision trees, and neural networks.
• Explain the concepts of overfitting and underfitting.
• Evaluate and validate machine learning models effectively.