NLP

Natural Language Processing enables computers to understand, interpret, and generate human language through advanced algorithms and machine learning. Modern NLP systems power chatbots, sentiment analysis, and automated content generation across industries.

Top 30+ NLP Use Cases with Real-life Examples

NLPNov 5

The NLP market will hit $53.42 billion this year. By 2031? We’re looking at $201.49 billion. 6. Automatic text summarization Text summarization moved past just pulling key sentences. Modern systems generate new text that captures essence without copying phrases. Extractive methods grab important sentences directly. Abstractive approaches write fresh summaries.

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The Future of Large Language Models

Interest in large language models (LLMs) is rising since ChatGPT attracted over 200 million monthly visitors in 2024.LLMs along with generative AI have an influence on a variety of areas, including medical imaging analysis and high-resolution weather forecasting.

NLPAug 22

In-depth Guide to Knowledge Graph: Use Cases

Your organization has data everywhere: customer databases, financial systems, HR records, project files, and emails. But when you need to answer “Which customers bought Product X and also had support tickets last month?” you’re stuck searching multiple systems, copying data to Excel, and hoping you didn’t miss anything. This data chaos costs companies millions.

NLPJul 25

Top 5 Natural Language Platforms (NLP) Comparison

There are numerous API providers in the chatbot landscape, with the majority focusing on Natural Language Processing (NLP) and Natural Language Understanding (NLU). It is a crucial decision to make, as this will affect the most important aspect of a conversational interface. We compared the top five natural language processing platforms and their features.