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Increasing the efficiency of claims processing and precise risk assessment
Through dida's expertise in the field of natural language processing (NLP) we succeeded in creating a software for the legal review of rental agreements.
With machine learning and NLP: Read about the development of software for the automatic verification of settlements using artificial intelligence.
Machine learning and information extraction: dida's AI-based algorithm simplifies business registrations through intelligent semantic search.
By Emilius Richter • July 18th, 2022
For a software provider, the project proposal is the first step toward meeting the needs of the customer. In this article, I will describe the most important modules in machine learning project proposals.
By Marty Oelschläger (PhD) • December 20th, 2021
Learn more about the ethics in natural language processing (NLP), the societal impact of machine learning (ML) & why caution should be exercised.
By Fabian Gringel • October 24th, 2021
Expand your knowledge about GPT-3 and read here about opportunities, weaknesses & troubleshooting as well as alternatives of the AI-based language model.
By Fabian Gringel • September 27th, 2021
Read here about how GPT-3 works, as well as its dangers & applications, and learn how you can try a GPT-3-like model for free.
By Emilius Richter • May 21st, 2021
Read about the 21 relevant questions that should be considered & answered upfront to start a successful machine learning software project.
By Angela Maennel • April 26th, 2021
Read here about how open domain question answering systems work & how they can improve your website's search function.
By Lovis Schmidt • August 17th, 2020
Comparison of the open source Python PDF text extraction tools PyPDF2, pdfminer & PyMuPDF. Read about tools for extracting text from PDF files here.
By Fabian Gringel • March 30th, 2020
Find out about the best free labeling tools for natural language processing (NLP) text annotation, installation & configuration.
