Natural Language Processing (NLP) has become a frequent topic of discussion in Data Science. In industry, we come across massive amounts of text data that needs to be properly analyzed using NLP techniques to fulfil certain business requirements. Feature extraction is one of the most important steps in NLP by which the context of words/tokens can be extracted. In this workshop we investigate the ability to extract context from text data in different embedding approaches including simple bag of word-based techniques as well as dense neural network-based techniques.