SKU/Artículo: AMZ-B0BW9BRVH3
Natural Language Understanding with Python: Combine natural language technology, deep learning, and large language models to create human-like language comprehension in computer systems
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Kindle
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Fuera de stock
Fuera de stock
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0.76 kg
0.76 kg
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Nuevo
Nuevo
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Amazon
Amazon
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USA
USA
Sobre este producto
- Build advanced NLU systems by utilizing NLP libraries such as NLTK, SpaCy, BERT, and OpenAI; ML libraries like Keras, scikit-learn, pandas, TensorFlow, and NumPy, along with visualization libraries such as Matplotlib and Seaborn.Purchase of the print Kindle book includes a free PDF eBook 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 DescriptionNatural Language Understanding facilitates the organization and structuring of language allowing computer systems to effectively process textual information for various practical applications. Natural Language Understanding with Python will help you explore practical techniques for harnessing NLU to create diverse applications. with step-by-step explanations of essential concepts and practical examples, you’ll begin by learning 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 discover practical issues such as acquiring data, evaluating systems, and deploying NLU applications along with their solutions. The book is a comprehensive guide that’ll help you explore techniques and resources that can be used for different applications in the future.By the end of this book, you’ll be well-versed with the concepts of natural language understanding, deep learning, and large language models (LLMs) for building various AI-based applications.What you will learnExplore the uses and applications of different NLP techniquesUnderstand practical data acquisition and system evaluation workflowsBuild cutting-edge and practical NLP applications to solve problemsMaster NLP development from selecting an application to deploymentOptimize NLP application maintenance after deploymentBuild a strong foundation in neural networks and deep learning for NLUWho this book is forThis 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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