Use a real-life example of an AI system to discuss some impacts of cyber attacks : Introduction to Machine Learning Task

The video introduces machine learning tasks, emphasizing the importance of understanding them before addressing security concerns. It covers supervised and unsupervised learning, detailing categories like classification, regression, clustering, dimensionality reduction, generative models, and reinforcement learning. Each category's vulnerabilities are highlighted, with examples such as road sign detection and stock price prediction. The video concludes with a focus on reinforcement and active learning, setting the stage for the next video on attacks against machine learning.

What is the primary difference between supervised and unsupervised machine learning?

• Unsupervised learning uses labeled data, while supervised learning does not.

• Supervised learning uses labeled data, while unsupervised learning does not.

• Neither uses labeled data.

• Both use labeled data but in different ways.

Which machine learning task is typically used for predicting stock prices?

• Classification

• Dimensionality Reduction

• Regression

• Clustering

How does clustering differ from classification?

• Classification requires labeled data, clustering does not.

• Both require labeled data.

• Clustering requires labeled data, classification does not.

• Neither requires labeled data.

What is the purpose of dimensionality reduction in machine learning?

• To increase the number of features in a dataset.

• To reduce the number of features in a dataset.

• To classify data into different categories.

• To predict future data points.

What is a key characteristic of reinforcement learning?

• It relies on labeled data.

• It focuses on reducing data dimensions.

• It is driven by an environment and adapts through trial and error.

• It uses clustering to organize data.