The Fitness Factory App aims to enhance its platform by integrating machine learning capabilities to provide personalized fitness recommendations to users. The project involves designing and developing a machine learning model that can analyze user data, such as workout history, preferences, and goals, to generate tailored fitness plans. The goal is to improve user engagement and satisfaction by offering more relevant and effective fitness guidance. This project provides learners with the opportunity to apply their knowledge of machine learning algorithms, data preprocessing, and model evaluation. The tasks are closely related and focus on the development and integration of a machine learning model within the existing app infrastructure. The project is designed to be completed by a team of learners from a computer science or data science program, ensuring they have the necessary skills to tackle the challenge.

The project deliverables include a fully functional machine learning model integrated into the Fitness Factory App, capable of generating personalized fitness recommendations. The team will also provide documentation detailing the model's architecture, data preprocessing steps, and evaluation metrics. Additionally, a presentation summarizing the project's outcomes and the model's impact on user engagement will be required. These deliverables will demonstrate the learners' ability to apply classroom knowledge to a real-world application, showcasing their skills in machine learning development and integration.