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 need to understand 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 like road sign detection and stock price prediction. The video concludes with a reminder of the importance of understanding these tasks to identify vulnerabilities, and a preview of the next video on attacks against machine learning.

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

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

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

• Both use labeled data but in different ways.

• Neither uses labeled data.

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

• Dimensionality Reduction

• Classification

• Regression

• Clustering

In which task is the information about data classes unknown?

• Generative Models

• Clustering

• Regression

• Classification

What is the main goal of generative models in machine learning?

• To reduce the dimensionality of data

• To classify data into predefined categories

• To simulate data based on existing data

• To predict future data points

How does reinforcement learning primarily differ from active learning?

• Active learning is environment-driven, while reinforcement learning involves a teacher.

• Both involve a teacher guiding the learning process.

• Reinforcement learning is environment-driven, while active learning involves a teacher.

• Both are environment-driven with no external guidance.