Natural language processing (NLP), a branch of artificial intelligence, addresses the understanding of human language (both in written and spoken form) by computers. As a scientific discipline, NLP covers tasks such as determining sentence structures and boundaries in documents, detecting keywords or phrases in audio recordings, inferring relationships between documents, and uncovering meaning in informal or slang speech patterns. NLP can make it possible to analyze oral data and recognize patterns that are not currently structured.
NLP holds the key to enabling major advances in text analysis and gaining deeper and potentially more powerful insights from social media data streams where slang or non-traditional language is prevalent.
NLP tokenization (NLP Tokenization) is the process of dividing raw text into “tokens”, which are small units that can be processed by machine learning models in natural language processing.
Data matching is the process of linking a data field from one source to a data field from another source.
Demand forecasts help make the right business decisions by predicting future demands for products and services. Demand forecasts cover finely detailed data, historical sales data, surveys and more.
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