Regression Models Code Templates

This repository contains code templates for various regression models in machine learning. Each template is structured for easy use and understanding, with comments explaining each part of the code.

Contents

• Simple Linear Regression
• Multiple Linear Regression
• More models will be added over time.

How to Use

Each folder contains:

• Notebook (.ipynb): The code template for the specific regression model.
• Dataset (.csv): Example data used in the model (if applicable).

Simple Linear Regression

The simple_linear_regression folder contains a template for fitting a simple linear regression model to a dataset. This example uses a dataset that correlates years of experience with salary.

Code Walkthrough:

• Import Libraries: Imports necessary libraries (numpy, matplotlib, pandas, scikit-learn).
• Dataset: Reads the Salary_Data.csv file which contains two columns: YearsExperience and Salary.
• Splitting Data: Splits the data into training and test sets.
• Training: Trains a linear regression model on the training set.
• Prediction: Uses the model to predict the test set results.
• Visualization: Plots the training and test set results.

Important: Change Your CSV (Data)

If you are using your own dataset, don't forget to:

1. Replace the CSV file: You should replace the provided Salary_Data.csv with your own CSV file.

2. Modify the Code: Ensure that the CSV file path in the code matches your new file. For example:

   dataset = pd.read_csv('Your_Dataset.csv')