Funding entity Cátedra Santalucía de Analytics for Education
This project is a collaborative initiative proposed by the Instituto de Investigación Tecnológica (IIT) with the Cátedra Santalucía de Analytics for Education.
The project's main goal is to create a functional application designed in R, allowing interactive data analysis. The application will facilitate the understanding of complex datasets through advanced neural network techniques and the NeuralSens interpretability framework. This tool aims to support educational and research purposes, particularly for students and researchers in data science fields.
The application will be distributed among students at Universidad Pontificia Comillas and Cátedra Santalucía, supporting their learning and research activities. It will facilitate advanced data analysis and model interpretability, contributing to the fields of machine learning and data science.
Key Features and Deliverables
- Interactive Analysis: The application will include features for importing data, training linear and neural network models, and performing sensitivity analysis.
- NeuralSens Methodology: Incorporates the NeuralSens methodology for detailed data interpretation and model understanding.
- User Interface: The tool will have a user-friendly interface with components such as a top bar for primary functions, a sidebar for dataset and model management, and a main panel for detailed data views and model summaries.
- Data Import and Preparation: Supports CSV and XLSX file formats for data import, with detailed guides for data preparation to ensure compatibility and ease of use.
- Training and Analysis: Provides functionalities for training both linear and neural network models, with options for advanced configurations like cross-validation and hyperparameter tuning.
Layman's summary: The project aims to create an interactive application using neural networks and the NeuralSens methodology for enhanced data analysis and interpretability. This tool will aid students and researchers in understanding complex datasets through advanced neural network techniques.
SantaLucia_App_2024
