Showing results for "Natural Language Processing with Python Steven Bird English"

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 co...

This book is a perfect beginner's guide to natural language processing. It is offering an easy to understand guide to implementing NLP techniques using Python. Natural language processing has been around for more than fifty years, but just recently with greater amounts of data present and better computational powers, it has gained a greater popularity.Given the importance of data, there is no wonder why natural language processing is on the rise. I...

PrefaceIntroduction to the BookMastering Natural Language Processing with Python and NLTKWelcome to "Mastering Natural Language Processing with Python and NLTK." This book is a comprehensive guide designed to introduce you to the world of Natural Language Processing (NLP) using Python and its most renowned library, NLTK. Whether you are a student, a data scientist, a linguist, or a curious mind, this book aims to equip you with the tools and knowledge to delve into ...

Learn NLP with Python through practical exercises, advanced topics like transformers, and real-world projects such as chatbots and dashboards. A comprehensive guide for mastering NLP techniques.Key FeaturesA comprehensive guide to processing, analyzing, and modeling human language with PythonReal-world projects that reinforce NLP concepts, including chatbot design and sentiment analysisFoundational and advanced NLP techniques for practical appl...

Build and deploy intelligent applications for natural language processing with Python by using industry standard tools and recently popular methods in deep learningKey FeaturesA no-math, code-driven programmer’s guide to text processing and NLPGet state of the art results with modern tooling across linguistics, text vectors and machine learningFundamentals of NLP methods from spaCy, gensim, scikit-learn and PyTorchBook Description...

This book offers a comprehensive and application-oriented exploration of Artificial Intelligence (AI) and Natural Language Processing (NLP), addressing both foundational principles and modern, data-driven methodologies. It is designed to equip readers with a deep understanding of how intelligent systems learn from data, interpret human language, and support automated decision-making across real-world contexts.Natural Language Processing for Business and Organizations: Research ...

This textbook provides a contemporary and comprehensive overview of Natural Language Processing (NLP), covering fundamental concepts, core algorithms, and key applications such as AI chatbots, Large Language Models and Generative AI. Additionally, it includes seven step-by-step NLP workshops, totaling 14 hours, that offer hands-on practice with essential Python tools, including NLTK, spaCy, TensorFlow, Keras, Transformers, and BERT.The objective of this book is to provide readers w...

This textbook presents an up-to-date and comprehensive overview of Natural Language Processing (NLP), from basic concepts to core algorithms and key applications. Further, it contains seven step-by-step NLP workshops (total length: 14 hours) offering hands-on practice with essential Python tools like NLTK, spaCy, TensorFlow Kera, Transformer and BERT.The objective of this book is to provide readers with a fundamental grasp of NLP and its core technologies, and to enable them to bui...

Foster your NLP applications with the help of deep learning, NLTK, and TensorFlowKey FeaturesWeave neural networks into linguistic applications across various platformsPerform NLP tasks and train its models using NLTK and TensorFlowBoost your NLP models with strong deep learning architectures such as CNNs and RNNsBook DescriptionNatural language processing (NLP) has found its application in various domains, such as web search...

Who would be liable for any mistakes machines make, and who would deal with the consequences? What is the current state of the art, what needs to be different, and what can be done? The gist of translation: how long will it be before machines make the web multilingual? How do you distinguish between past tense verb and present tense word? Language identification: how do you distinguish similar languages?Defining, designing, creating, and implementing a process to solve a challenge ...

Learn to harness the power of AI for natural language processing, performing tasks such as spell check, text summarization, document classification, and natural language generation. Along the way, you will learn the skills to implement these methods in larger infrastructures to replace existing code or create new algorithms.Applied Natural Language Processing with Python starts with reviewing the necessary machine learning concepts before moving onto discussing various NLP...

Get to grips with solving real-world NLP problems, such as dependency parsing, information extraction, topic modeling, and text data visualizationKey FeaturesAnalyze varying complexities of text using popular Python packages such as NLTK, spaCy, sklearn, and gensimImplement common and not-so-common linguistic processing tasks using Python librariesOvercome the common challenges faced while implementing NLP pipelinesBook Descriptio...