Free Download Natural Language Understanding with Python: Combine natural language technology, deep learning, and large language models to create human-like language comprehension in computer systems by Deborah A. Dahl
English | June 30, 2023 | ISBN: 1804613428 | 326 pages | PDF | 17 Mb
Build advanced Natural Language Understanding Systems by acquiring data and selecting appropriate technology.
Key FeaturesMaster NLU concepts from basic text processing to advanced deep learning techniquesExplore practical NLU applications like chatbots, sentiment analysis, and language translationGain a deeper understanding of large language models like ChatGPTBook Description
Natural language understanding (NLU) organizes and structures, language allowing computer systems to effectively process textual information for many different practical applications. Natural Language Understanding with Python will help you explore practical techniques that make use of NLU to build a wide variety of creative and useful applications.
Complete with step-by-step explanations of essential concepts and practical examples, this book begins by teaching you about NLU and its applications. You'll then explore a wide range of current NLU techniques and their most appropriate use-case. In the process, you'll be introduced to the most useful Python NLU libraries. Not only will you learn the basics of NLU, you'll also be introduced to practical issues such as acquiring data, evaluating systems, and deploying NLU applications, along with their solutions. This book is a comprehensive guide that will help you explore the full spectrum of essential NLU techniques and resources.
By the end of this book, you will be familiar with the foundational concepts of NLU, deep learning, and large language models (LLMs). You will be well on your way to having the skills to independently apply NLU technology in your own academic and practical applications.
What you will learnThe most important skill that readers will acquire is not just HOW to apply natural language techniques, but WHY to select particular techniques.The book will also cover important practical considerations concerning acquiring real data and evaluating real system performance, not just performing textbook evaluations with pre-existing corporaAfter reading this book and studying the code, readers will be equipped to build state of the art as well as practical natural language applications to solve real problems.How to develop and fine-tune an NLP applicationMaintaining NLP applications after deploymentWho this book is for
This book is for python developers, computational linguists, linguists, data scientists, NLP developers, conversational AI developers, and students looking to learn about natural language understanding (NLU) and applying natural language processing (NLP) technology to real problems. Anyone interested in addressing natural language problems will find this book useful. Working knowledge in Python is a must.
Table of ContentsNatural Language Understanding, Related Technologies, and Natural Language ApplicationsIdentifying Practical Natural Language Understanding ProblemsApproaches to Natural Language Understanding - Rule-Based Systems, Machine Learning, and Deep LearningSelecting Libraries and Tools for Natural Language UnderstandingNatural Language Data - Finding and Preparing DataExploring and Visualizing DataSelecting Approaches and Representing DataRule-Based TechniquesMachine Learning Part 1 - Statistical Machine LearningMachine Learning Part 2 - Neural Networks and Deep Learning TechniquesMachine Learning Part 3 - Transformers and Large Language ModelsApplying Unsupervised Learning ApproachesHow Well Does It Work? - EvaluationWhat to Do If the System Isn't WorkingSummary and Looking to the Future
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