“Today a reader, tomorrow a leader.”
― Margaret Fuller
Natural Language Processing (NLP) is a field of artificial intelligence that focuses on the interaction between computers and human languages. It involves building models that enable machines to understand, interpret, and generate natural language, facilitating human-computer communication. NLP combines computational linguistics and machine learning to process and analyze large amounts of text or speech data.
NLP tasks range from simple applications like tokenization and part-of-speech tagging to more complex ones such as machine translation, sentiment analysis, and question answering. Key techniques include statistical methods, rule-based systems, and, more recently, deep learning models like Recurrent Neural Networks (RNNs), Transformers, and Large Language Models (LLMs), which have significantly advanced the field.
NLP plays a crucial role in various applications like virtual assistants, chatbots, language translation, and content recommendation systems. Its ability to derive meaning and context from human language has transformed industries, allowing for more intelligent and human-like interactions between machines and users.
Other material
Stanford CS224N: Natural Language Processing with Deep Learning
A popular course from Stanford that dives deep into modern NLP with a focus on deep learning.
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