Introduction To Natural Language Processing With Python
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Natural Language Processing with Python
Author: Steven Bird
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2009-06-12
This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication. Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.
Introduction to Natural Language Processing with Python
Author: Linsel Tadashi
language: en
Publisher: Independently Published
Release Date: 2025-03-31
Dive into the world of Natural Language Processing (NLP) with Introduction to Natural Language Processing with Python. This comprehensive guide is perfect for beginners who want to learn how to process and analyze human language using Python. Whether you're a data scientist, a software developer, or simply curious about the power of NLP, this book provides a step-by-step approach to mastering key NLP techniques using popular libraries like NLTK and SpaCy. NLP is at the core of applications like chatbots, sentiment analysis, language translation, and more. By learning how to apply NLP techniques in Python, you'll be able to unlock the potential of working with text data, performing text analysis, and building intelligent systems that can understand and generate human language. Inside, you'll learn: The fundamentals of NLP and how it fits into machine learning and AI How to install and use the NLTK (Natural Language Toolkit) and SpaCy libraries Techniques for tokenization, stemming, and lemmatization How to process text data for sentiment analysis, classification, and information extraction Working with word embeddings and vectorization methods like TF-IDF Building and training NLP models for tasks like text classification and language generation Real-world examples and projects, such as building a text-based chatbot By the end of this book, you'll have a strong understanding of NLP concepts and hands-on experience using Python to process and analyze text data. Whether you want to improve your data science skill set or develop language-processing applications, Introduction to Natural Language Processing with Python will give you the tools you need to get started. Key Features: Learn NLP from the basics with easy-to-follow instructions and examples Master popular Python libraries like NLTK and SpaCy for NLP tasks Step-by-step guidance on text processing, classification, and sentiment analysis Real-world projects and applications of NLP techniques Best practices for working with text data in Python Start your NLP journey today with Introduction to Natural Language Processing with Python and unlock the power of human language data!
Natural Language Processing
Natural language processing (NLP) is about developing applications and services that are able to understand human languages. In this perfect Natural Language Processing Tutorial, we will use Python NLTK library. Natural language toolkit (NLTK) is the most popular library for natural language processing (NLP) which was written in Python and has a big community behind it. This is the Ultimate guide to learn Natural Language Processing (NLP) basics, such as how to identify and separate words, how to extract topics in a text. You dont need a big and a boring book to start today . Get Your Copy Now!!Book ObjectivesThe book objectives include the following: To help you appreciate big data as a great source of information and knowledge. To help you understand natural language processing. To help you know how to use natural language processing to extract knowledge and information from big data. To help you learn how to implement natural language processing solutions using NLTK (Natural Language Processing Toolkit) and other libraries in Python. Who this Book is for? Do you belong to any of the following categories? You are a complete beginner to natural language processing. You want to learn Python programming for natural language processing. You want to advance your skills in Python for natural language processing. Professors, lecturers or tutors who are looking to find better ways to explain Natural Language Processing to their students in the simplest and easiest way. Students and academicians, especially those focusing on python programming, Neural Networks, Machine Learning, Deep Learning, and Artificial Intelligence. If yes, this is the right book for you. What do you need for this Book? You only have to have installed Python 3.X on your computer. The author guides you on how to install the rest of the libraries on your computer. What is inside the book? GETTING STARTED WITH NATURAL LANGUAGE PROCESSING TEXT WRANGLING AND CLEANSING. REPLACING AND CORRECTING WORDS. TEXT CLASSIFICATION. SENTIMENT ANALYSIS. PARSING STRUCTURE IN TEXT. SOCIAL MEDIA MINING. NLTK FOR SENTIMENT ANALYSIS. SCIKIT-LEARN FOR TEXT CLASSIFICATION. WORK WITH PDF FILES IN PYTHON. WORK WITH TEXT FILES IN PYTHON. WORD2VEC ALGORITHM. NLP APPLICATIONS From the back cover.This comprehensive guide covers both statistical and symbolic approaches to Natural Language Processing. This is a good introduction to all the major topics of computational linguistics, which includes automatic speech recognition and processing, machine translation, information extraction, and statistical methods of linguistic analysis. Indeed, Natural Language Processing is the scientific discipline concerned with making the natural language accessible to machines, and it is a necessary means to facilitate text analytics by establishing structure in unstructured text to enable further analysis. This guide is a fundamental reference for any computational linguist, speech scientist or language data scientist. The explanations and illustrations in this short book are very intuitive and simple. The author helps you understand what natural language processing is. This is basically a theory touching on the fundamentals of natural language processing. The author then explains to you what the NLTK library is and what it does. The rest of the book is about implementing natural language processing tasks using the NLTK library in Python. Samuel Burns uses a combination of theory, Python code examples, and screenshots showing the expected outputs for various program codes.