# Introduction to Machine Learning, ML Introduction Series Part1

> Source: <https://blog.stackademic.com/introduction-to-machine-learning-ml-introduction-series-part1-53a1e19463d4?source=rss----d1baaa8417a4---4>
> Published: 2026-07-06 14:33:01+00:00

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# Introduction to Machine Learning, ML Introduction Series Part1

**Overview of Human Learning & Machine Learning**

A general definition of Machine Learning is:

“Machine learning is the field of study that gives computers the ability to learn without being explicitly programmed.”

— *Arthur Samuel, 1959*

So, Machine Learning is the science (and art) of programming computers so they can learn from data.

To understand this concept, let us look at how a programmatic solution(Classic Algorithm) differs from a machine learning solution.

In the Classic approach, we write the program on a computer and provide input to it. Then the program runs and produces an output.

In the ML approach, we feed the data and an example of output (Input-Output pairs in the form of a Dataset) into the computer. Here, the programmer does not need to write the program(or very little program); rather, the computer itself learns from the given input-output pairs and returns the program/model.

**Example: Spam Filter**

If you want to build an ML algorithm to detect whether an email is spam or ham (not spam), you have to provide some existing examples of spam and ham emails.

**Input:** Emails**Output:** Whether the mail is spam or ham

By learning from these input-outputs, a model will be developed that will…