Machine Learning I

Slides¶

Lecture Video¶

This lecture has been recorded using Zoom. You need to use your NUS email to login. Please access the Zoom recording use the links below:

• Recording from AY2024/2025 Sem 2 (Passcode: @j.#99+y)

Content¶

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

Learning Objectives¶

• Understand basic concepts and types of machine learning.

• Differentiate between supervised and unsupervised learning.

• Recognize importance of data preprocessing in machine learning.

• Identify various machine learning models such as linear regression, logistic regression, decision trees, and neural networks.

• Explain concepts of overfitting and underfitting.

• Evaluate and validate machine learning models effectively.