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Applied Natural Language Processing in the Enterprise - Teaching Machines to Read, Write, and Understand (Paperback) Loot Price: R1,379
Discovery Miles 13 790
Applied Natural Language Processing in the Enterprise - Teaching Machines to Read, Write, and Understand (Paperback): Ankur...

Applied Natural Language Processing in the Enterprise - Teaching Machines to Read, Write, and Understand (Paperback)

Ankur Patel, Ajay Arasanipalai

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Loot Price R1,379 Discovery Miles 13 790 | Repayment Terms: R129 pm x 12*

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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, youâll learn how to train and deploy real-world NLP 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 Use Python and PyTorch to build core parts of the NLP pipeline from scratch, including tokenizers, embeddings, and language models Take your models out of Jupyter notebooks and learn how to deploy, monitor, and maintain them in production

General

Imprint: O'Reilly Media
Country of origin: United States
Release date: May 2021
Authors: Ankur Patel • Ajay Arasanipalai
Dimensions: 233 x 178 x 21mm (L x W x T)
Format: Paperback
Pages: 350
ISBN-13: 978-1-4920-6257-8
Categories: Books
LSN: 1-4920-6257-X
Barcode: 9781492062578

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