NLP Learning Series: Part 4 - Transfer Learning Intuition for Text Classification

This post is the fourth post of the NLP Text classification series. To give you a recap, I started up with an NLP text classification competition on Kaggle called Quora Question insincerity challenge. So I thought to share the knowledge via a series of blog posts on text classification. The first post talked about the different preprocessing techniques that work with Deep learning models and increasing embeddings coverage. In the second post , I talked through some basic conventional models like TFIDF, Count Vectorizer, Hashing, etc. that have been used in text classification and tried to access their performance to create a baseline. In the third post , I delved deeper into Deep learning models and the various architectures we could use to solve the text Classification problem. In this post, I will try to use ULMFit model which is a transfer learning approach to this data.

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