Skip to content

Latest commit

 

History

History
40 lines (30 loc) · 880 Bytes

README.md

File metadata and controls

40 lines (30 loc) · 880 Bytes

Restaurant-Revenue-Prediction

This repository contains a Machine Learning project about Restaurant revenue prediction, made by four 4th year Software engineering students made using python - jupyter notebook.

The predictions were made using 6 popular Machine Learning.

Table of Contents

  1. Environment Setup

    • Importing Libraries
    • Loading the Data
  2. Initial Assessment

    • Overview
    • Descriptive Statistics
  3. Data Processing

    • Basic Cleanup
    • Missing Values
    • Outlier Detection
  4. Feature Engineering

    • Working with Date and Time Variables
    • Handling Outliers - Feature Scaling
    • Categorical Encoding
  5. Correlation Analysis

  6. Models

    • Linear Regression
    • KNN
    • Random Forest
    • SVM
    • Decision Tree
    • Clustering (Extra)
  7. Model Evaluation

    • Model Comparison
    • Model Evaluation
  8. Conclusion