Nowadays, a growing volume of data is generated from various sources, such as sensors and social media, making data storage and management increasingly challenging. Extracting valuable insights from this raw data to support decision-making requires data mining methods, especially when combined with machine learning (ML) algorithms to uncover hidden patterns. This work presents the development of an integrated platform that combines a scientific data repository with ML tools, data science methods, and resources for geographic data visualization. The platform enables users to implement complete pipelines—from data storage and management to ML model training and deployment—streamlining workflows and making data science more accessible to a broader audience. Key features include a dataset repository, classic ML algorithms for tabular data, and new deep learning algorithms for image classification. The new model-sharing module facilitates collaboration by allowing users to share and manage trained models within the platform.