The Conference for Machine Learning Innovation

How to turn large amounts of text into insights with machine learning

Workshop
Join the ML Revolution!
Register until October 20:
✓ Save up to $233
✓ Team discount
✓ Extra Specials for Freelancers
Register Now
Join the ML Revolution!
Register until October 20:
✓ Save up to $233
✓ Team discount
✓ Extra Specials for Freelancers
Register Now
Join the ML Revolution!
Register until November 03:

✓ Save up to €494
✓ 10% Team Discount✓ Special discount for freelancers
Register Now
Join the ML Revolution!
Register until November 03:

✓ Save up to €494
✓ 10% Team Discount✓ Special discount for freelancers
Register Now
Join the ML Revolution!
Until the Conference starts:
✓ Group discount
✓ Special discount for freelancers
Register Now
Join the ML Revolution!
Until the Conference starts:
✓ Group discount
✓ Special discount for freelancers
Register Now

Lots of important information in companies are only available in text form. Methods of automated text analysis methods help to leverage this treasure trove of knowledge. Whether user-generated content from the web, customer inquiries by mail, or contracts and specifications: A lot of information is available in form of unstructured texts. As this volume of data grows ever faster, it is no longer possible to simply "read along". The solution is to automate the processing and analysis of such documents. NLP, clustering, topic modeling, classification, universal embeddings – there are currently many different AI technologies for the automated processing of text volumes. Some of these technologies solve very different problems and can achieve their greatest performance in combination. 


The speaker will use a concrete example to explain the stages of a text analytics project and show which techniques are suitable for which areas of application and which new use cases are thus possible. The session is aimed at developers, business users, managers and data science beginners who want to better assess the potential of automated text analysis for their own applications.

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This Session belongs to the Diese Session gehört zum Programm vom MunichMunich program. Take me to the program of . Hier geht es zum Programm von Berlin Berlin .

Take me to the full program of Zum vollständigen Programm von Munich Munich .

This Session Diese Session belongs to the gehört zum Programm von MunichMunich program. Take me to the current program of . Hier geht es zum aktuellen Programm von Singapore Singapore , Berlin Berlin or oder Munich Munich .

Behind the Tracks