A project employing an autoencoder model to analyze the Adult Data Set from the UCI Machine Learning repository and predict missing information based on dataset trends, such as predicting occupation based on age and income. Comprehensive dataset splitting was conducted to allocate parts of the dataset as training, validation, and testing data to ensure fairness and accuracy of the model and reduce bias.