The project aims to develop a sentiment analysis tool that can evaluate customer feedback for 9406-7725 Quebec Inc. The company receives a significant amount of customer feedback through various channels, and understanding the sentiment behind this feedback is crucial for improving customer satisfaction and product offerings. The goal is to create a machine learning model that can accurately classify feedback as positive, negative, or neutral. This project will allow learners to apply their knowledge of natural language processing (NLP) and machine learning algorithms. The tasks will include data collection, data preprocessing, model training, and evaluation. The project will focus on creating a prototype that can be integrated into the company's existing feedback system.

The deliverables for this project include a well-documented sentiment analysis model and a report detailing the methodology and results. The team will also provide a presentation demonstrating the model's functionality and potential integration points. Additionally, a user guide will be created to assist in the deployment and use of the model within the company's feedback system.