Book Woofer

Led a team of Data Scientists to enhance reading with music Built and deployed an application that evaluates text and plays music alongside the mood classification. Utilised Spotify and IMDb APIs to gather information. Used Natural Language Processing (NLP): Employed Machine Learning techniques by building pipelines to find the optimal results. Use of NLTK libraries and Word2Vec Trained and optimised various Deep Learning models, including Convolutional Neural Network, Recurrent Neural Network and BERT/Roberta architectures. Final model was developed using the RNN library. Frontend platform built using Streamlit and deployed on Heroku. https://book-woofer.herokuapp.com