Natural Language processing is used in an abundance of domains; Gateway was the core of our new product, which is designed to translate day-to-day Iraqi dialect then deploy them into real-world scenarios. NLP combines computational linguistics—rule-based modeling of human language—with statistical, machine learning, and deep learning models. Together, these technologies enable computers to process human language in the form of text and to ‘understand’ its full meaning.
NLP drives computer programs that translate text from one language to another and summarize large volumes of text rapidly—even in real time.
Natural language processing helps computers communicate with humans in their own language and scales other language-related tasks.
It helps resolve ambiguity in language and adds useful numeric structure to the data for many downstream applications.
Different techniques for interpreting human language, ranging from statistical and machine learning methods to rules-based and algorithmic approaches.
NLP tasks break down language into shorter, elemental pieces, try to understand relationships between the pieces and explore how the pieces work together to create meaning.