Create Confusion Matrix

# Introduction

In this project, you will learn how to implement a confusion matrix, which is a fundamental tool for evaluating the performance of a classification model. The confusion matrix provides a detailed breakdown of the model's predictions, allowing you to identify areas for improvement and gain valuable insights into the model's strengths and weaknesses.

## 🎯 Tasks

In this project, you will learn:

- How to implement the `confusion_matrix` function to compute the confusion matrix for a classification problem
- How to test and refine the `confusion_matrix` function to handle edge cases and improve its robustness
- How to document the `confusion_matrix` function to make it more user-friendly and easier to understand
- How to integrate the `confusion_matrix` function into a larger machine learning project and use it to evaluate the performance of a classification model

## 🏆 Achievements

After completing this project, you will be able to:

- Compute and interpret the confusion matrix for a classification problem
- Apply techniques for handling edge cases and improving the robustness of a function
- Implement best practices for documenting and making code more user-friendly
- Apply the confusion matrix in the context of a larger machine learning project