Think of your favorite NLP application that you wish to build - sentiment analysis, named entity recognition, machine translation, information extraction, summarization, recommender system, to name a few. A key step to building it is - using the right technique to represent the text in a form that machine can understand. In this workshop, we will understand key concepts, maths, and code behind state-of-the-art techniques for text representation.
This workshop is meant for NLP enthusiast, ML practitioners, Data science teams who often work with text data and wish to gain a deeper understanding of text representations for NLP. This will be a very hands-on workshop with jupyter notebooks to create various representations, coupled with the key concepts & maths that forms the basis of their respective theory.
Deep Learning in Images has had a phenomenal success story. One of the key reasons for it is: Rich representation of data - raw image in matrix form with RGB values.