What is machine learning, and how does it work?

What is machine learning?

One definition: “Machine learning is the semi-automated extraction of knowledge from data”

• Knowledge from data: Starts with a question that might be answerable using data
• Automated extraction: A computer provides the insight
• Semi-automated: Requires many smart decisions by a human

What are the two main categories of machine learning?

Supervised learning: Making predictions using data

• Example: Is a given email “spam” or “ham”?
• There is an outcome we are trying to predict

Unsupervised learning: Extracting structure from data

• Example: Segment grocery store shoppers into clusters that exhibit similar behaviors
• There is no “right answer”

How does machine learning “work”?

High-level steps of supervised learning:

1. First, train a machine learning model using labeled data
2. Then, make predictions on new data for which the label is unknown

The primary goal of supervised learning is to build a model that “generalizes”: It accurately predicts the future rather than the past!