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Sách Applied Natural Language Processing in the Enterprise Teaching Machines to Read, Write, and Understand

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Sách Applied Natural Language Processing in the Enterprise Teaching Machines to Read, Write

Sách keo gáy, bìa mềm
 
NLP has exploded in popularity over the last few
years. But while Google, Facebook, OpenAI, and others continue to
release larger language models, many teams still struggle with building
NLP applications that live up to the hype. This hands-on guide helps you
get up to speed on the latest and most promising trends in NLP.
With
a basic understanding of machine learning and some Python experience,
you'll learn how to build, train, and deploy models for real-world
applications in your organization. Authors Ankur Patel and Ajay Uppili
Arasanipalai guide you through the process using code and examples that
highlight the best practices in modern NLP.
• Use state-of-the-art
NLP models such as BERT and GPT-3 to solve NLP tasks such as named
entity recognition, text classification, semantic search, and reading
comprehension
• Train NLP models with performance comparable or superior to that of out-of-the-box systems
• Learn about Transformer architecture and modern tricks like transfer learning that have taken the NLP world by storm
• Become familiar with the tools of the trade, including spaCy, Hugging Face, and fast.ai
Build core parts of the NLP pipeline--including tokenizers, embeddings,
and language models--from scratch using Python and PyTorch
• Take your models out of Jupyter notebooks and learn how to deploy, monitor, and maintain them in production
 
Categories:Computers - Computer Science
 
Year:2021
 
Edition:1
 
Language:english
 
Pages:336
 

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