Verlag: O'Reilly Media (edition 1), 2021
ISBN 10: 149206257X ISBN 13: 9781492062578
Sprache: Englisch
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In den WarenkorbPaperback. Zustand: 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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In den WarenkorbPaperback. Zustand: 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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In den WarenkorbPaperback. Zustand: 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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In den WarenkorbKartoniert / Broschiert. Zustand: 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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Taschenbuch. Zustand: 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.
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In den WarenkorbPaperback. Zustand: 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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Zustand: Gut. Zustand: Gut | Sprache: Englisch | Produktart: Bücher.
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