Food Delivery Time Prediction

By analyzing historical data and considering factors such as distance, traffic conditions, and order preparation time, the project seeks to provide reliable predictions for delivery times.
The system utilizes a range of input variables such as the distance between the restaurant and the customer's ___location, current traffic conditions, order preparation time, and the ratings of the delivery personnel. These factors are fed into a machine learning model, which has been trained on a dataset of past delivery records, to generate predictions.

Dataset:

Food Delivery Dataset

Libraries Used For The Project:

1. numpy
2. pandas
3. matplotlib
4. seaborn
5. haversine
6. sklearn
7. xgboost

Models Used:

1. Linear Regression
2. Lasso Regression
3. Decision Tree Regressor
4. XGB Regressor
5. Random Forest Regressor