From 9206950e319329c7fedda1c7dbaf1d659c8ab495 Mon Sep 17 00:00:00 2001 From: Paskal Date: Sun, 1 Jun 2025 23:04:42 +0545 Subject: [PATCH] word changed in Readme.md --- 2-Regression/3-Linear/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/2-Regression/3-Linear/README.md b/2-Regression/3-Linear/README.md index c9060034..61220eba 100644 --- a/2-Regression/3-Linear/README.md +++ b/2-Regression/3-Linear/README.md @@ -9,7 +9,7 @@ So far you have explored what regression is with sample data gathered from the pumpkin pricing dataset that we will use throughout this lesson. You have also visualized it using Matplotlib. -Now you are ready to dive deeper into regression for ML. While visualization allows you to make sense of data, the real power of Machine Learning comes from _training models_. Models are trained on historic data to automatically capture data dependencies, and they allow you to predict outcomes for new data, which the model has not seem before. +Now you are ready to dive deeper into regression for ML. While visualization allows you to make sense of data, the real power of Machine Learning comes from _training models_. Models are trained on historic data to automatically capture data dependencies, and they allow you to predict outcomes for new data, which the model has not seen before. In this lesson, you will learn more about two types of regression: _basic linear regression_ and _polynomial regression_, along with some of the math underlying these techniques. Those models will allow us to predict pumpkin prices depending on different input data.