The objective of this project is to develop an AI-powered sentiment analysis tool that can accurately assess and categorize the sentiment of textual data. This tool will help 9406-7725 Quebec Inc. better understand customer feedback, social media interactions, and other text-based communications. The project will involve training a machine learning model using a dataset of labeled text samples. Learners will apply their knowledge of natural language processing (NLP) and machine learning algorithms to create a model that can classify text into positive, negative, or neutral sentiment categories. The project will also include developing a user-friendly interface for inputting text data and displaying sentiment results. This project provides an opportunity for learners to apply classroom knowledge in AI and machine learning to a real-world application, enhancing their understanding of NLP techniques and model evaluation.

The deliverables for this project include a trained sentiment analysis model capable of classifying text data into sentiment categories with a specified accuracy level. Additionally, a user interface will be developed to allow users to input text and view sentiment analysis results. A comprehensive project report detailing the model development process, dataset used, and evaluation metrics will also be provided. This report will serve as documentation of the project's methodology and outcomes.