A Gentle Introduction to Machine Learning

Artificial Intelligence (AI) and Machine Learning (ML) are everywhere today, from the recommendations on your Netflix homepage to the spam filter in your email. But what do these terms actually mean?

What is Machine Learning?

In traditional programming, you provide the computer with data and rules (the program), and the computer gives you the answers.

In Machine Learning, the paradigm is flipped. You provide the computer with data and the answers, and the computer figures out the rules.

Key Types of Machine Learning

1. Supervised Learning: The algorithm is trained on labeled data. For example, feeding it thousands of pictures labeled “cat” or “not cat” until it can accurately identify cats in new images.
2. Unsupervised Learning: The algorithm is given unstructured data and tasked with finding patterns. For example, grouping customers by purchasing behavior without prior labels.
3. Reinforcement Learning: The algorithm learns by trial and error, receiving rewards for good actions. This is how many AI game-playing agents are trained.

Machine learning is a vast field, but fundamentally it relies on statistics, calculus, and massive amounts of data.