This is a semester project financial sentiment analysis using text feature extraction and text classification tech- niques. The objective is to classify each document (basically a sentence) of the given corpus into positive, negative or neutral categories.
Established end-to-end pipline leveraging Sickit-learn, TensorFlow and Keras libraries for financial sentiment analysis using NLP and Deep Learning of textual data collected from social media and news websites, deploying Transformers, Stacked RNN, LSTM, and Feed Forward Neural Nets.