Natural Language Processing (NLP)

Natural language processing

Natural language processing (NLP) is a field that combines linguistics, computer science, and artificial intelligence to enable computers to process and analyze human language. The ultimate aim is to develop computers that can understand the meaning of documents, extract information from them, and categorize and organize the documents effectively. Key challenges in NLP include speech recognition, understanding natural language, and generating natural language.

3 courses cover this concept

CS 230 Deep Learning

Stanford University

Fall 2022

An in-depth course focused on building neural networks and leading successful machine learning projects. It covers Convolutional Networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. Students are expected to have basic computer science skills, probability theory knowledge, and linear algebra familiarity.

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CS 224V Conversational Virtual Assistants with Deep Learning

Stanford University

Fall 2022

This course focuses on the creation of effective, personalized, conversational assistants using large language neural models. It involves both theory and practical assignments, offering students a chance to design their own open-ended course project. Familiarity with NLP and task-oriented agents is beneficial.

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CS1410 Artificial Intelligence

Brown University

Fall 2022

CS1410 at Brown University delves into the realm of Artificial Intelligence. Using the 3rd edition of "Artificial Intelligence, A Modern Approach" by Russell & Norvig, students explore intelligent agents, game theory, knowledge representation, logic, probabilistic learning, NLP, robotics, computer vision, and ethical implications of AI.

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