This workshop presents the full development cycle of an AI assistant for healthcare, detailing data curation, libraries for parameter optimization (model fine-tuning), and the application of fine-tuning. In the practical stage, participants run real-time inference with the fine-tuned model, validating its performance. The activity is structured to transform technical concepts into a functional...
This introductory Machine Learning (ML) workshop presents, in 60 minutes, the essential pillars for building predictive models. It covers initial variable exploration, criteria for feature selection, data splitting, and comparison between different algorithms. The goal is to provide a clear and practical overview of the ML workflow, enabling participants to understand the technical decisions...
https://doi.org/10.1186/s12859-026-06431-1
