Deep Learning

In this project, a Recurrent Neural Network (RNN) model was developed to classify tweets as complaints or non-complaints directed towards airlines. The project involved several steps, starting with data acquisition, where tweets were downloaded and extracted. Preprocessing steps included cleaning the text by removing URLs, converting mentions and hashtags, eliminating numbers and punctuation, and applying lemmatization. The data was then tokenized and sequenced for model input.

In this project, we dive into the subjective world of human attractiveness, using the power of deep learning to tackle a question as old as time: "Am I hot or not?" Leveraging a dataset of over 200,000 celebrity faces from the CelebFaces Attributes Dataset (CelebA), each annotated with binary attributes including "Attractive," our model—dubbed BeautyAI—aims to predict the allure of a face.