Course Content

Linear Regression for ML

1. Simple Linear Regression

What is Linear Regression Finding the Parameters Building the Linear Regression with scikit-learn Challenge Cheatsheet

2. Multiple Linear Regression

Linear Regression with Two Features Linear Regression with n Features Building Multiple Linear Regression Challenge Cheatsheet

3. Polynomial Regression

Quadratic Regression Polynomial Regression PolynomialFeatures Building the Polynomial Regression Interpolation vs Extrapolation Challenge Cheatsheet

4. Evaluating and Comparing Models

Metrics

Challenge

For this challenge, the same housing dataset will be used.
However, now it has two features: age and area of the house (columns age and square_feet).


              1234
            
import pandas as pd

df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/b22d1166-efda-45e8-979e-6c3ecfc566fc/houseprices.csv')
print(df.head())

Your task is to build a Multiple Linear Regression model using the OLS class. Also, you will print the summary table to look at the p-values of each feature.

Task

Assign the 'age' and 'square_feet' columns of df to X.
Build and train the model using the LinearRegression class.
Predict the target for X_new.

Task

Assign the 'age' and 'square_feet' columns of df to X.
Build and train the model using the LinearRegression class.
Predict the target for X_new.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Section 2. Chapter 4

Challenge

For this challenge, the same housing dataset will be used.
However, now it has two features: age and area of the house (columns age and square_feet).


              1234
            
import pandas as pd

df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/b22d1166-efda-45e8-979e-6c3ecfc566fc/houseprices.csv')
print(df.head())

Your task is to build a Multiple Linear Regression model using the OLS class. Also, you will print the summary table to look at the p-values of each feature.

Task

Assign the 'age' and 'square_feet' columns of df to X.
Build and train the model using the LinearRegression class.
Predict the target for X_new.

Task

Assign the 'age' and 'square_feet' columns of df to X.
Build and train the model using the LinearRegression class.
Predict the target for X_new.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Section 2. Chapter 4

Challenge

For this challenge, the same housing dataset will be used.
However, now it has two features: age and area of the house (columns age and square_feet).


              1234
            
import pandas as pd

df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/b22d1166-efda-45e8-979e-6c3ecfc566fc/houseprices.csv')
print(df.head())

Your task is to build a Multiple Linear Regression model using the OLS class. Also, you will print the summary table to look at the p-values of each feature.

Task

Assign the 'age' and 'square_feet' columns of df to X.
Build and train the model using the LinearRegression class.
Predict the target for X_new.

Task

Assign the 'age' and 'square_feet' columns of df to X.
Build and train the model using the LinearRegression class.
Predict the target for X_new.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

For this challenge, the same housing dataset will be used.
However, now it has two features: age and area of the house (columns age and square_feet).


              1234
            
import pandas as pd

df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/b22d1166-efda-45e8-979e-6c3ecfc566fc/houseprices.csv')
print(df.head())

Your task is to build a Multiple Linear Regression model using the OLS class. Also, you will print the summary table to look at the p-values of each feature.

Task

Assign the 'age' and 'square_feet' columns of df to X.
Build and train the model using the LinearRegression class.
Predict the target for X_new.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Section 2. Chapter 4

Switch to desktop for real-world practiceContinue from where you are using one of the options below