Our project selection was motivated by a deep-seated interest in the machine learning aspects it entailed. Our aim was to harness the power of predictive modeling, and we were equally drawn to the intricate problem-solving demands of this specific scenario. Notably, the absence of readily available data piqued our curiosity as it required us to construct our own dataset and employ customized techniques to address this challenge. As we embarked on this project, our knowledge expanded significantly. We gained proficiency in the art of creating a dataset from scratch, a skill that dovetailed seamlessly with our foray into predictive modeling. Additionally, we ventured into the realm of web development, mastering the creation of a website tailored to facilitate project managers' access to comprehensive asset information through intuitive dashboards. To ensure systematic progress, we divided our project into three distinct milestones. Each milestone was entrusted to a dedicated team member: one for dataset development, another for predictive model construction, and a third for web application development. However, this project was not without its formidable challenges, primarily because it marked our inaugural foray into a hackathon, catching us somewhat unprepared for the multifaceted adversities we encountered. Foremost among these challenges was the dearth of data, necessitating its generation and meticulous refinement to align with our specific requirements and the company's needs. Furthermore, grappling with the intricacies of predictive modeling presented a formidable learning curve, as it was the first encounter with such a program or application for all team members. Yet, our collective commitment and unwavering communication within the team proved instrumental in devising effective solutions to the best of our abilities.
Built With
- next.js
- python
- tailwind
- vercel
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