The advent of Generative Large Language Models (LLMs) has revolutionized a myriad of business operations, ranging from creating enthralling blog articles to the brilliant classification of sentiments across statements. These models, when spiced with tailored datasets,...
In a previous post, we conducted a comprehensive benchmark on the role of synthetic text generation for intent detection using traditional Natural Language Understanding (NLU) platforms. In that study, we specifically examined the performance of Rasa as an example,...
In previous posts, we have outlined the crucial role of Machine Learning for Analytics (in How to Make Machine Learning more Effective using Linguistic Analysis?), and the implications of using Machine Learning for analyzing and structuring text (in How Phrase...
This post dives into one of the topics of a previous post “How to Make Machine Learning more effective using Linguistic Analysis”. We referred to the strong points of Machine Learning technology for insight extraction. We also stated that text analysis is...
Text analysis is becoming a pervasive task in many business areas. Machine Learning is the most common approach used in text analysis, and is based on statistical and mathematical models. Linguistic approaches, which are based on knowledge of language and its...
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