Introduction to Machine Learning

The video provides a basic understanding of machine learning, focusing on its ability to find patterns in data to make predictions. It uses examples like credit card fraud detection to illustrate how patterns are identified and used. The video also explains the architecture of machine learning, including algorithms and models, and clarifies the relationship between artificial intelligence and machine learning, highlighting that machine learning is a subset of AI.

What is the primary function of machine learning as described in the introduction?

• To store large amounts of data

• To find patterns in data and predict future events

• To replace human decision-making

• To create new data from scratch

Why is it challenging to identify accurate patterns with small datasets?

• Small datasets are always accurate

• Small datasets often lead to incorrect patterns

• Small datasets are too complex

• Small datasets are too expensive to analyze

What is the role of algorithms in machine learning?

• To find patterns in data and create models

• To store data

• To visualize data

• To delete unnecessary data

What is a model in the context of machine learning?

• A visualization tool

• A function or code used to recognize patterns in new data

• A physical representation of data

• A type of data storage

What are 'features' in machine learning?

• The labels of a dataset

• The output of a model

• The errors in a dataset

• The columns used to find patterns

How is machine learning related to artificial intelligence?

• They are completely unrelated

• Machine learning is the only form of AI

• Machine learning is a type of AI

• AI is a subset of machine learning

Which statement is true about AI and machine learning?

• Machine learning is a subset of AI

• All AI is machine learning

• AI and machine learning are the same

• Machine learning is broader than AI