# Introduction to Machine Learning: How We Arrive at Linear Regression
The article introduces the concept of Machine Learning and its relation to Linear Regression. It explains how Machine Learning allows computers to learn from data rather than following explicit programming rules. The article also outlines the types of Machine Learning and the significance of regression problems in predicting continuous numerical values.
- ▪Machine Learning is a branch of Artificial Intelligence that teaches computers to learn patterns from data.
- ▪There are three main types of Machine Learning: supervised, unsupervised, and reinforcement learning.
- ▪Linear Regression is a supervised learning algorithm used to predict continuous values by finding relationships between input and output variables.
Opening excerpt (first ~120 words) tap to expand
try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3708630) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Stacy Omwoyo Posted on May 23 # Introduction to Machine Learning: How We Arrive at Linear Regression #beginners #python #datascience #machinelearning Before we talk about Linear Regression, we first need to understand the bigger idea it belongs to Machine Learning. Machine Learning is the reason applications today can: recommend movies on Netflix, suggest products on Amazon, recognize faces on your phone, and even predict house prices or exam scores.
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