Python Text Analysis: Word Embeddings

Word Embeddings How can we use neural networks to create meaningful representations of words? The bag-of-words is limited in its ability to characterize text, because it does not utilize word context. In this part, we study word embeddings, which were among the first attempts to use neural networks to develop numerical representations of text that incorporate context. We learn how to use the package gensim to construct and explore word embeddings of text.

Prerequisites: Python Text Analysis Fundamentals: Parts 1-2

Workshop Materials: https://github.com/dlab-berkeley/Python-Text-Analysis

Software Requirements: Installation Instructions for Python Anaconda

Is Python Not working on your laptop? Attend the workshop anyway, we can provide you with a cloud-based solution until you figure out the problems with your local installation.