What a data scientist to do if they lack sufficient data or suffer from extreme imbalanced dataset to train a deep learning model?

The answer definitely is using IBM’s Lambada AI generates training data for text classifiers. Here is an full implementation of the paper ‘Not Enough Data? Deep Learning to the Rescue!‘ with code.

Natural language processing (NLP) is the technique to provide semantics to information extracted from optical character recognition engines and documents. In this article, we progress from reviewing the recent history of natural language processing towards a deeper understanding of information understanding through NLP.

We will look at the history, biggest open problems and frontiers methodology.

Machine learning with natural language is faced with one major hurdle – its algorithms usually deal with numbers, and natural language is, well, text. So we need to transform that text into numbers, otherwise known as text vectorization.