_{Thomas M. Siebel Professor in Machine learning, Professor of linguistics and computer science, Director, Stanford Artificial Intelligence Laboratory (SAIL), Associate Director, Human-Centered Artificial Intelligence Institute, Stanford University. Ph.D. Stanford.}

_{Henry and Gertrude Rothschild Professor of Computer Science and Founding Director of Columbia’s Data Science Institute at Columbia University. Ph.D. - University of Pennsylvania.}

_{Distinguished Professor and Director of the Center for Data Science in the College of Information and Computer Sciences at the University of Massachusetts Amherst., Ph.D. - University of Rochester.}

Natural Language Processing (NLP) is a field of artificial intelligence that deals with the interaction between computers and human languages. It involves the use of computational techniques to analyze, understand, and generate human language. It is a subfield of computer science and has applications across a wide range of industries, including healthcare, finance, transportation, and manufacturing.

NLP is used to perform a wide range of tasks, including text mining, sentiment analysis, language translation, and speech recognition.

Text mining, also known as text analytics, is the process of extracting meaningful information from unstructured text data. This can be used for applications such as sentiment analysis, which involves identifying the sentiment or opinion expressed in a piece of text.

Language translation is another important application of NLP. It involves converting text from one language to another, which is useful for applications such as language learning and international business.

Speech recognition is also an important application of NLP. It involves converting spoken language into text, which is useful for applications such as voice-controlled assistants and dictation software.

NLP is also used in natural language generation, which involves generating text that is grammatically correct and semantically meaningful. This can be used for applications such as chatbots and automated text summarization.

NLP is also used in named entity recognition, which is the process of identifying and extracting named entities from text, such as people, organizations, and locations. This can be used in various applications such as news analytics, social media monitoring, and customer service chatbot.

In recent years, deep learning techniques have been applied to NLP, leading to significant improvements in the performance of NLP systems. These techniques include recurrent neural networks (RNNs) and transformer-based models, and they are used in a wide range of NLP tasks such as language understanding and text-to-speech synthesis.

Overall, NLP is a rapidly evolving field with many exciting developments and advancements. It is expected to have a significant impact on a wide range of industries and applications in the future, including language translation, sentiment analysis, and speech recognition.