Explainable AI Models for Any Topic with Novelty

Explainable AI Models for Any topic with novelty Project Description: Build a complete end-to-end Machine Learning project using dataset (CSV) to identify the source of infection using Explainable AI models. The project should include data loading, EDA (missing values, distributions, correlations, visualizations), data preprocessing (handling missing data, encoding categorical features, scaling numeric data, removing outliers), and feature selection. Train and compare multiple ML models with cross-validation and hyperparameter tuning, and include explainability using SHAP (SHapley Additive exPlanations) and LIME (Local Interpretable Model-agnostic Explanations). Deploy the system with a Streamlit web UI where users can upload datasets, select the target column, run preprocessing, train models, view EDA visualizations, see model results, make predictions, and download the trained model and pipeline. You must also suggest and add additional technologies, models, or ideas to improve the project’s novelty and performance.

Projektin tunnus (ID): 40281309