Introduction

This project will examine the food and beverage industry with a particular emphasis on the time it takes for food delivery services to give clients with the meals they have requested. By precisely projecting delivery timeframes, we may improve customer transparency by utilising machine learning algorithms. Our model examines past data, in particular how long it used to take delivery partners to travel the similar distances in the past.

Food Delivery Time Prediction

Real-time delivery time prediction is what we want to achieve. The first thing we'll do is figure out how far the meal preparation location is from the consumption point. We will first calculate the distance between the delivery location and the restaurant. In order to comprehend the relationship between the time required by delivery partners over comparable distances in the past, we will next examine the historical data.

--

Files Included

1. Food Delivery Prediction ML Model: Basic Analysis of Dataset is done in Jupyter Notebook,
2. Dataset: Both .txt and .csv files are added. I used .txt file in the project.
3. ML_Model_FD: I used Google Colab for building the ML model and testing it. I had to switch from Jupyter Notebook due to storage issues. However, Google Colab worked perfectly.

--