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NLPeasy - a Workflow to Analyse, Enrich, and Explore Textual Data


Use pre-trained NLP-models, ingest into Elastic Search, and enjoy auto-generated Kibana dashboards!

Ever wanted to try out NLP methods but it felt it too cumbersome to set up a workflow for textual data? How to enrich your data based on textual features and explore the results?

NLPeasy ( does that: Enrich the data using well-known pre-trained models (Word embeddings, Sentiment Analysics, POS, Dependency Parsing). Then start the Elastic Stack on your Docker. Set-up indices and ingest it in bulk. And finally generate Kibana dashboards to explore the results.

Complicated? Not at all! Just do it in a simple Jupyter Notebook.

In this presentation we will give an architecture overview of the different components and demonstrate the capabilities of this Python package.

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