What Is Machine Learning?

Machine Learning (ML) is the subfield of artificial intelligence that enables computers, without us writing every rule one by one, to learn patterns from data and produce predictions and decisions. Classic software is "rule-based"; ML, on the other hand, derives a model from examples.

How Does Machine Learning Work?

In the traditional approach, we write the rule "If A, then B". In ML, the model is given many examples; the model statistically learns the relationship between inputs and outputs. Afterwards, when a new data point arrives, it produces "the most likely outcome".

Core Types of Machine Learning

• Supervised Learning: Learns from labeled data. (E.g., "This is a cat / this is a dog")
• Unsupervised Learning: Finds similarity clusters in unlabeled data. (E.g., customer segmentation)
• Reinforcement Learning: Develops strategies via reward-penalty. (E.g., game agents, route optimization)

Where Will You See It?

Recommendation systems, spam filters, fraud detection, demand forecasting, dynamic pricing… The engine behind most automation that looks "smart" is ML.