We have been inspired by HP, thanks to the challenge they proposed during the HackUPC event presentation.
Our proyect generates 13 images for each of the 100 objects of the dataset given. Moreover, taht images are shown in a web page.
We carried out an analysis of the HP system, preprocessed the provided dataset, and constructed a model that predicts the stock of a product in a specific week.
Understanding the HP system, knowing how to relate the company's idiosyncrasy with the dataset, cleaning the dataset, and building the model for inference are crucial steps in this process.
Having understood the functioning of the system that HP possesses, being able to propose a solution to a real problem, and achieving good results supported by metrics are key aspects of the project.
Fighting against real-life problems and being able to navigate the field of data science for the first time.
Developing the study of new data preprocessing techniques and conducting in-depth research on different models is a commendable endeavor.