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7 results for natural language processing

Infrastructure

Core ML

Core ML is Apple's on-device machine learning framework that enables iOS, macOS, watchOS, and tvOS applications to integrate pre-trained models for tasks including image classification, natural language processing, and sound analysis.

5 min readUpdated June 2026
Applications

Named Entity Recognition

Named entity recognition (NER) is a natural language processing task that identifies and classifies named entities in text — such as people, organisations, locations, and dates — into predefined categories.

6 min readUpdated May 2026
Foundations

Natural Language Processing

Natural language processing (NLP) is the subfield of AI concerned with enabling computers to understand, interpret, manipulate, and generate human language in both text and speech form.

3 min readUpdated May 2026
Applications

Question Answering

Question answering is the natural language processing task of producing accurate answers to questions posed in natural language, often using information retrieval, reading comprehension, or large language models.

5 min readUpdated May 2026
Applications

Sentiment Analysis

Sentiment analysis is a natural language processing technique that automatically identifies and classifies the emotional tone of text as positive, negative, or neutral, and is widely used in customer feedback, social media monitoring, and financial analysis.

6 min readUpdated May 2026
Applications

Text Summarisation

Text summarisation is the natural language processing task of producing a shorter version of a document that preserves its key information, using extractive or abstractive techniques.

4 min readUpdated May 2026
Foundations

Tokenisation

Tokenisation is the process of breaking text into discrete units called tokens — which may represent words, subwords, characters, or symbols — that serve as the fundamental input units for language models and other natural language processing systems.

6 min readUpdated May 2026