Online Food Order Feedback Prediction using RNN
This project aims to predict the feedback (positive or negative) of online food orders using Recurrent Neural Networks (RNN) with Long Short-Term Memory (LSTM) cells. The model analyzes various features related to the online food orders and predicts whether the feedback will be positive or negative.
Utilizing cutting-edge machine learning methodologies, our primary goal is to furnish precise and dependable feedback forecasts to empower decision-making across the online food industry.
By conducting thorough data analysis, model refinement, and validation, our objective is to furnish stakeholders with a robust solution for enhancing customer satisfaction, operational efficiency, and strategic decision-making in response to evolving feedback dynamics.