Customer Satisfaction Prediction Model

This Jupyter Notebook demonstrates a simple Multiple Variable linear regression model to predict customer satisfaction based on multiple parameters. It includes functions to compute the model output, plot the data, visualize the model's predictions, normalizing data, feature scaling, calculating gradient descent etc. Contents

Importing necessary libraries
Defining the training data
Plotting the data points
Computing model output
Visualizing the results

Requirements

Python 3.12.0
Jupyter Notebook
numpy
matplotlib

How to Run Install the required packages using pip:

pip install -r requirements.txt

Open the Jupyter Notebook:

jupyter notebook one.ipynb

Run the cells in the notebook to see the implementation and results.

Files

model.ipynb: The main Jupyter Notebook containing the code and explanations.
requirements.txt: List of required Python packages.