A very common confusion among those new to machine learning is the difference between a machine learning algorithm and a Model in machine learning. The two terms are often used interchangeably, which makes it even more confusing. So in this article, I will tell you what is the difference between algorithm and model in machine learning.

Is There a Difference Between Algorithm and Model?

My answer will be Yes, as a machine learning algorithm is like a procedure executed on data to find patterns and rules that are stored and used to create a machine learning model that is like a program that can be used to make predictions.

Also, Read – Machine Learning Skills You Must Know.

What is an Algorithm?

A machine learning algorithm is essentially a procedure that is used to find patterns within data and learn from the data. It is commonly said to be fit on a dataset which means it is applied on the dataset.

There are many types of algorithms with many different functions and purposes. The three main ones are:

• Regression: Used to make predictions where the output is a continuous value, such as logistic regression.
• Classification: are those algorithms that are used to classify between the categorical values.
• Clustering: Used to group similar items or clustered data points, such as K-Means.

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