Classifying Mental Illness on Social Media using BERT Github

Given the current scenario, millions suffer from mental illnesses and increasingly turn to online platforms to express themselves. To identify such cases, we developed a BERT-based architecture to identify five main kinds of mental illnesses- depression, anxiety, bipolar disorder, ADHD, and PTSD by analyzing unstructured user data on Reddit. Experimented with various architectures and variants of BERT, including Roberta, Deberta, and Electra. The final proposed pipeline comprises an Ensemble of BERT to give the most accurate prediction

SNAP Recommendation Engine

Graph-Based Recommendation Engine that recommends appropriate similar products, co-purchased products, and high confidence products similar to one viewed by the user using the Amazon SNAP Co-Purchasing Dataset.Used NetworkX, Dask, and Pandas for the back-end and Streamlit for the front-end for the demo