What are word embeddings?

Word embeddings are a powerful technique from computational linguistics, where words are represented as vectors in a two-dimensional space. These vectors capture the meaning and relationships of words based on the context in which they appear. This enables you to gain a deeper understanding of language and how you can use computers to process this information.

In this workshop, you'll jump right into the practical work. 

You will learn…

You'll get to know the theory and gain hands-on experience. After this workshop, you'll be able to independently analyze corpora, identify connections between words and their meanings, and visualize data to uncover new insights. This knowledge opens up countless possibilities in text analysis and natural language processing.

In a nutshell, you will gain the ability to:

• Upload and prepare a corpus for analysis in Jupyter Notebook.
• Calculate the semantic similarity between words using cosine similarity.
• Discover word analogies through vector operations.

What you need to do beforehand? 

We ask you to download AnacondaExternal link prior to the workshop so that you can get started immediately in Jupyter Notebook.