Applied Natural Language Processing by Patel Ankur (32 results)

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  • Language: English

    Published by O'Reilly Media, 2021

    149206257X / 9781492062578

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    paperback. Condition: Acceptable. Please see the condition note after this for details, if this is missing please consider Acceptable to mean poor quality that could include major staining, water damage, writing, missing dustjacket, etc etc. Our books are dispatched from a Yorkshire former cotton mill. We list via barcode/ISBN so please note that the images are stock images and may not be the exact copy you receive, furthermore the details about edition and year might not be accurate as many publishers reuse the same ISBN for multiple editions and as we simply scan a barcode or enter an ISBN we do not check the validity of the edition data when listing. If you're looking for an exact edition please don't order (at least not without checking with us first, although we don't always have time to check). We aim to dispatch prompty, the service used will depend on order value and book size. We can ship to most countries, see our shipping policies. Payment is via Abe only.

  • Language: English

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    Paperback. Condition: Very Good. 1. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

  • Language: English

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  • Language: English

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    paperback. Condition: Very Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority.

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  • Language: English

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  • Language: English

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  • Language: English

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  • Language: English

    Published by O'Reilly Media 6/1/2021, 2021

    149206257X / 9781492062578

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    Paperback or Softback. Condition: New. Applied Natural Language Processing in the Enterprise: Teaching Machines to Read, Write, and Understand. Book.

  • Language: English

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    Paperback. Condition: New. 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 comprehensionTrain NLP models with performance comparable or superior to that of out-of-the-box systemsLearn about transformer architecture and modern tricks like transfer learning that have taken the NLP world by stormBecome familiar with the tools of the trade, including spaCy, Hugging Face, and fast.aiUse Python and PyTorch to build core parts of the NLP pipeline from scratch, including tokenizers, embeddings, and language modelsTake your models out of Jupyter notebooks and learn how to deploy, monitor, and maintain them in production.

  • Language: English

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  • Language: English

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  • Language: English

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    Paperback. Condition: New. 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 comprehensionTrain NLP models with performance comparable or superior to that of out-of-the-box systemsLearn about transformer architecture and modern tricks like transfer learning that have taken the NLP world by stormBecome familiar with the tools of the trade, including spaCy, Hugging Face, and fast.aiUse Python and PyTorch to build core parts of the NLP pipeline from scratch, including tokenizers, embeddings, and language modelsTake your models out of Jupyter notebooks and learn how to deploy, monitor, and maintain them in production.

  • Language: English

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    Paperback. Condition: new. Paperback. NLP is one of the hottest topics in AI today. Having lagged for years behind other deep learning fields such as computer vision, NLP only recently gained mainstream popularity. Google, Facebook, and OpenAI have open-sourced large pretrained language models, but many organizations today still struggle with building and adopting NLP applications. This hands-on guide helps you learn the process quickly.If you have a basic to intermediate understanding of machine learning and programming experience with Python, you'll learn how to build and deploy real-world NLP applications in your organization. Authors Ankur Patel and Ajay Uppili Arasanipalai walk you through the process without bogging you down in theory.Understand how state-of-the-art NLP models work Learn the tools of the trade, including frameworks popular today Perform NLP tasks such as text classification, semantic search, and reading comprehension Solve problems using new models like transformers and techniques such as transfer learning Build NLP models from scratch with performance comparable or superior to out-of-the-box systems Deploy your models to production and maintain their performance Implement a suite of NLP algorithms using Python and PyTorch" This hands-on guide helps you get up to speed on the latest and most promising trends in NLP. With some Python experience and a basic understanding of machine learning, you'll learn how to build and deploy real-world NLP applications in your organization. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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    Paperback. Condition: Brand New. 350 pages. 9.19x7.00x0.70 inches. In Stock.

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    Paperback. Condition: New. 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 comprehensionTrain NLP models with performance comparable or superior to that of out-of-the-box systemsLearn about transformer architecture and modern tricks like transfer learning that have taken the NLP world by stormBecome familiar with the tools of the trade, including spaCy, Hugging Face, and fast.aiUse Python and PyTorch to build core parts of the NLP pipeline from scratch, including tokenizers, embeddings, and language modelsTake your models out of Jupyter notebooks and learn how to deploy, monitor, and maintain them in production.

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    Condition: New. This hands-on guide helps you get up to speed on the latest and most promising trends in NLP. With some Python experience and a basic understanding of machine learning, you ll learn how to build and deploy real-world NLP applications in your organization.

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    Condition: Gut. Zustand: Gut | Seiten: 333 | Sprache: Englisch | Produktart: Bücher | NLP is one of the hottest topics in AI today. Having lagged for years behind other deep learning fields such as computer vision, NLP only recently gained mainstream popularity. Google, Facebook, and OpenAI have open-sourced large pretrained language models, but many organizations today still struggle with building and adopting NLP applications. This hands-on guide helps you learn the process quickly.If you have a basic to intermediate understanding of machine learning and programming experience with Python, you'll learn how to build and deploy real-world NLP applications in your organization. Authors Ankur Patel and Ajay Uppili Arasanipalai walk you through the process without bogging you down in theory.Understand how state-of-the-art NLP models workLearn the tools of the trade, including frameworks popular todayPerform NLP tasks such as text classification, semantic search, and reading comprehensionSolve problems using new models like transformers and techniques such as transfer learningBuild NLP models from scratch with performance comparable or superior to out-of-the-box systemsDeploy your models to production and maintain their performanceImplement a suite of NLP algorithms using Python and PyTorch.

  • Language: English

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    Paperback. Condition: New. 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 comprehensionTrain NLP models with performance comparable or superior to that of out-of-the-box systemsLearn about transformer architecture and modern tricks like transfer learning that have taken the NLP world by stormBecome familiar with the tools of the trade, including spaCy, Hugging Face, and fast.aiUse Python and PyTorch to build core parts of the NLP pipeline from scratch, including tokenizers, embeddings, and language modelsTake your models out of Jupyter notebooks and learn how to deploy, monitor, and maintain them in production.

  • Language: English

    Published by O'reilly Media Jun 2021, 2021

    149206257X / 9781492062578

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    Taschenbuch. Condition: Neu. Neuware - NLP is one of the hottest topics in AI today. Having lagged for years behind other deep learning fields such as computer vision, NLP only recently gained mainstream popularity. Google, Facebook, and OpenAI have open-sourced large pretrained language models, but many organizations today still struggle with building and adopting NLP applications. This hands-on guide helps you learn the process quickly.If you have a basic to intermediate understanding of machine learning and programming experience with Python, you'll learn how to build and deploy real-world NLP applications in your organization. Authors Ankur Patel and Ajay Uppili Arasanipalai walk you through the process without bogging you down in theory.- Understand how state-of-the-art NLP models work- Learn the tools of the trade, including frameworks popular today- Perform NLP tasks such as text classification, semantic search, and reading comprehension- Solve problems using new models like transformers and techniques such as transfer learning- Build NLP models from scratch with performance comparable or superior to out-of-the-box systems- Deploy your models to production and maintain their performance- Implement a suite of NLP algorithms using Python and PyTorch.