About This Book
Natural Language Processing (NLP) is a field within artificial intelligence that focuses on enabling
machines to understand, interpret, and generate human language. NLP bridges the gap between human
communication and computer understanding, allowing machines to process and analyze large amounts
of natural language data, such as text and speech. Its applications are widespread in industries like
healthcare, finance, customer service, and entertainment, impacting everything from chatbots to
translation services. At its core, NLP involves several key tasks, including tokenization, part-of-speech
tagging, named entity recognition (NER), and syntactic parsing. Tokenization breaks text into smaller
units, such as words or sentences, while part-of-speech tagging labels each word with its grammatical
role. Named entity recognition identifies entities like people, organizations, and locations, and syntactic
parsing analyzes the grammatical structure of sentences. Another important aspect of NLP is semantic
analysis, which focuses on understanding the meaning of words and sentences in context. Word
embeddings, such as Word2Vec and GloVe, represent words as vectors in a high-dimensional space,
capturing semantic relationships between words. Deep learning models like recurrent neural networks
(RNNs) and transformers have greatly advanced NLP by enabling machines to handle more complex
language tasks, such as sentiment analysis, machine translation, and text summarization. Overall, NLP
continues to evolve, pushing the boundaries of how machines interact with human language. Natural
Language Processing provides a comprehensive guide to the principles, techniques, and applications of
NLP, enabling machines to understand and interact with human language.
Contents: 1. Introduction, 2. Machine-based Neural Systems, 3. Sequential Neural Networks,
4. Automata Theory and Regular Languages, 5. Methods: Rules, Statistics, Neural Networks, 6. Neural
Models of Speech Production, 7. Typical Tasks in Natural Language Processing, 8. Machine Language,
9. Exploring Evolutionary and Neurolinguistic Sciences.
