Zero To Hero Machine Learning — Day 1

This article focuses on the definition of Machine Learning and makes a comparison between supervised and unsupervised learning.

For those of you who prefer to watch a video I made on my channel regarding my journey:

What is Machine Learning?

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

Supervised Learning

In supervised learning, we are given a data set and already know what our correct output should look like, having the idea that there is a relationship between the input and the output.

In this type of learning, problems can be categorized into “regression” and “classification” problems.

• In a regression problem, we are trying to predict results within a continuous output. For example, predicting the price of a house based on its size.
• In a classification problem, we are trying to predict results in a discrete output. For example, Given a patient with a tumor, we have to predict whether the tumor is malignant or benign.

Unsupervised Learning

In unsupervised learning, we are given a data set, and we don’t know what our correct output should look like. Instead of having labeled examples to learn from, the algorithm explores the data on its own, identifying inherent patterns, relationships, or clusters without explicit guidance.

For example, given a large collection of articles, using this type of learning you can analyze the text and automatically group similar articles together, revealing patterns or themes without any predefined labels.

Hope you enjoyed!!

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Link to a video regarding this subject on my YouTube channel: https://youtu.be/QANGqJpDCDE

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Link to a post regarding this subject on my blog: https://excali-blog.vercel.app/posts/software-engineer-learning-machine-learning/1