Machine learning and artificial intelligence is everywhere nowadays. All of the ads that you see on your instagram that seem to be too accurate and too tailored to you and your interests - that’s machine learning! The recommended products that you see while browsing your favorite shops on the internet - that’s machine learning!
According to Google, the definition of machine learning is:
“the use and development of computer systems that are able to learn and adapt without following explicit instructions, by using algorithms and statistical models to analyze and draw inferences from patterns in data.”
In more simple terms, it is the idea that a machine will learn from past events in order to make a prediction about the future. There are two main types of machine learning: unsupervised learning and supervised learning.
Supervised Learning
In supervised learning, the machine takes an input and an output and makes predictions based on the “right” answers.
There are two main types of supervised learning and those are regression and classification.
In regression, the computer learns to predict a number based on infinitely many possible numbers.
For example, let’s say we are given housing data and we want to predict how much a 2,500 sq. ft. house will sell for.
| Square footage | Selling Price |
|---|---|
| 1000 | 200,000 |
| 2000 | 300,000 |
| 3000 | 400,000 |
The square footage of the house is our input and the selling price of the house is the output and our “right” answer. So, the computer will make a prediction based on past sales.
In classification, the computer predicts a category or class such as if a tumor is malignant or benign.
Unsupervised Learning
In unsupervised learning, we have a bunch of unclassified and unlabeled data that the computer will try to make sense of and find something interesting.
Common types of unsupervised learning are clustering, anomaly detection, and dimensionality reduction. Clustering algorithms group similar items together based on patterns.
This article is the first of a machine learning series that will break down lots of machine learning topics so that you can add this topic to your data bank!