15 Things You Should Know About Spacy
Natural Language Processing with AI
The automatic evaluation of text data with artificial intelligence plays an increasingly important role. Valuable information can be lifted fully automatically and made available to users in a clearly arranged form. Research times can be shortened immensely.
spaCy is the state-of-the-art open source library for advanced Natural Language Processing (NLP) in Python.
It was developed specifically for productive use and is a great tool for building applications that process text and help to "understand" large text corpora.
The talk outlines fifteen key points to know about spaCy for better or worse and gives an insight into today's practical possibilities of NLP by means of a recent enterprise use case.
Presented at the EuroPython on July 23rd, 2020. EuroPython (est. 2002), one of the largest conferences for the Python language and related topics in data science and AI worldwide.
Key Takeaways & Use Case Presented
Use Case: Making Enterpise Knowdege Accessible Scalably
Our client has an extensive archive of research documents that vary considerably in format and quality. Unfortunately, the collected knowledge was not accessible in a structured way, common search methods only yielded partial results. Valuable knowledge could not be lifted, the danger of having to spend money again on researching already existing knowledge was enormous.
Our solution was to create a user interface that would allow the user to search the document base for different topics.
Keywords were automatically extracted from the existing text data and put into context.
Individual clusters can be easily explored in any depth.
Summaries of the documents were automatically generated and made available to the user during the search.
SpaCy was one of the open source software building blocks used in the project.
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Your Contact Person
Alexander Hendorf -
Alexander Hendorf is a renowned IT professional and expert in Big Data, Data Mining, Machine Learning and Artificial Intelligence. He is a frequent speaker at international conferences like PyData, PyCons or MongoDB World NYC.
After founding an independent label, Hendorf recognized the potential of digitalization for the music industry and began programming trading platforms and databases.
This combination of entrepreneurship and digitization is reflected in his consulting concepts. With a high level of expertise, he specializes in particular in process optimization through Agile Data Analytics and Data Value Assessments.
Hendorf is a Python Software Foundation Fellow, one of the chair persons of PyConDE and PyData Berlin, chair person of the German Python Softwareverband e.V and one of the 25 MongoDB Masters worldwide. Through his commitment to open source and his membership in corresponding global organizations, he also has an excellent international IT network.