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NLP Landscape: Switzerland

NLP People

It’s Institute of Computational Linguistics , which includes the Phonetics Laboratory , lead by Martin Volk and Volker Dellwo, as well as the URPP Language and Space perform research in NLP topics, such as machine translation, sentiment analysis, speech recognition and dialect detection. University of St. Gallen The University of St.

NLP 52
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Generative NLP Models in Customer Service: Evaluating Them, Challenges, and Lessons Learned in…

ODSC - Open Data Science

Generative NLP Models in Customer Service: Evaluating Them, Challenges, and Lessons Learned in Banking Editor’s note: The authors are speakers for ODSC Europe this June. Be sure to check out their talk, “ Generative NLP models in customer service. How to evaluate them?

NLP 52
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Using AI-Mechanized Hyperautomation for Organizational Decision Making

Unite.AI

Central to deep learning is the ML-based Neural Network algorithms, which have dramatically revolutionized the decision-making process at discrete data points on a quantum scale. It penetrates the big datadata input that is voluminous, scattered, and incomplete.

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Top 15 Data Analytics Projects in 2023 for beginners to Experienced

Pickl AI

5. Text Analytics and Natural Language Processing (NLP) Projects: These projects involve analyzing unstructured text data, such as customer reviews, social media posts, emails, and news articles. NLP techniques help extract insights, sentiment analysis, and topic modeling from text data.

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Leveraging user-generated social media content with text-mining examples

IBM Journey to AI blog

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. What is text mining? Text analysis takes it a step farther by focusing on pattern identification across large datasets, producing more quantitative results.

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Data Demystified: What Exactly is Data?- 4 Types of Analytics

Pickl AI

While unstructured data may seem chaotic, advancements in artificial intelligence and machine learning enable us to extract valuable insights from this data type. Big Data Big data refers to vast volumes of information that exceed the processing capabilities of traditional databases.

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Why Linguistics for Text Analysis?

Bitext

Recapping, the main limitation of Machine Learning for text analytics is that it is “blind” to text structure. And text structure is essential for moving towards text understanding. This is the first benefit Linguistics provides to data sicentists.