Machine Learning Tutorial 1 - Linear Regression on Boston Housing Dataset | Machine Learning Basics

In this video, we will learn about Linear regression with python machine learning. You are a real estate agent and you want to predict the house price. It would be great if you can make some kind of automated system which predicts the price of a house based on various inputs which are known as a feature. Supervised Machine learning algorithms need some data to train their model before making a prediction.

Solution:
Change the name of the r2_score list to r2Score to avoid the error. Then restart the kernel and run all. It should work. I had declared a list with the name r2_score that is why we are getting error.

#Linear_Regression #Machine_Learning #Boston_Housing
🔊 Watch till last for a detailed description
07:30 What is linear regression?
11:04 Simple linear regression
14:26 Multiple linear regression
20:40 How to determine error?
26:54 Get started with the problem statement
39:19 Understand your data
41:42 Data visualization
01:05:21 Pairplot and Corrmat of correlated data
01:11:14 Training the model
01:15:39 Evaluating performance of the model
01:33:01 Regression plot of the features correlated with house price
01:58:27 Defining performance metrics

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