Introduction to Word Embeddings

Author(s): Bharat Choudhary

Originally published on Towards AI.

Implementation of word embedding using deep learning for Natural Language processing.

Word Cloud from Kaggle

Word embedding is a method to capture the “meaning” of the word via low dimension vector and it can be used in a variety of tasks in Natural Language Processing (NLP).

Before beginning word embedding tutorial we should have an understanding of vector space and similarity matrix.

A sequence of numbers that is used to identify a point in space is called vector and if we have a whole bunch of vectors that all belong to the same dataset it will be called a vector space.

Words in the text can also be represented in the higher dimension in vector… Read the full blog for free on Medium.

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Published via Towards AI