Interactive Word Embeddings using Word2Vec and Plotly
In this 2 hour long project, you will learn how to preprocess a text dataset comprising recipes, and prepare the data for use in a word embedding model. You will learn how Word2Vec works, and how to implement this model using Gensim. You will learn about visualizing the results using a similarity matrix, and then build a network graph using NetworkX on top of this. You will learn how to build an visual tool to explore this data in a manner that is both interactive and aesthetically unmatched, using Plotly. This tool can then be used for interactive recommendations, or similar item discovery, for example, to be used in an online supermarket store recommending additional items to be purchased, or offering effective alternatives when there is no stock of a desired item.