Autores: Avila Perez-Grovas, Patricio
Etiquetas: this project focuses on the exploration, analysis, and extraction of relevant information from a dataset composed of the interaction between hundreds of anonymous users from a company. the dataset includes a wide range of information, including user communication details over a year, such as user and message identification, the exact moment each message was sent and received, among other relevant data.the main goal of the project is to acquire insights information from this dataset, using advanced and sophisticated data analysis techniques. mainly, we will focus on the application of clustering techniques to categorize users based on their usage.in addition, a detailed analysis of the data will be performed to estimate and predict users' schedules based on their past behavior. this approach will allow us to identify patterns and trends in user communication habits, which in turn could provide valuable information about their preferences and needs.this study will not only provide a deeper insight into user behavior but could also be a valuable tool for the company in making strategic decisions and improving its services. by better understanding their users, the company can design and implement more efficient and effective solutions to meet their needs., machine learning, predicting, productivity
