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Machine Learning basics in 5 minutes

3 min readJun 4, 2025

Machine learning is how machines learn to do stuff. Stuff could be predicting the next apocalypse or your grocery bill based on some data. It could also be your Spotify song recommendations or your next travel destination suggestion. In short, Machine learning is a process of training software called a model to perform tasks.

What is a model?

A model is a set of parameters and structure needed for a system to make predictions.

A machine takes a set of data called input and generates an output based on the input. Input (also known as a feature) is also called the independent variable because it’s not dependent on anything. Output is the dependent variable (also called labels because you put labels on the result)

Types of Machine Learning systems

ML systems can be broadly classified into the following types based on how they perform tasks:

Supervised learning
Unsupervised learning
Reinforcement learning
Generative AI

Supervised learning

Supervised learning is when a model is provided with input and output to understand the relationship between them. The model uses that understanding to…

Machine Learning basics in 5 minutes

What is a model?

Types of Machine Learning systems

Supervised learning

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