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    Natural Language Processing with AWS AI Services. Derive strategic insights from unstructured data with Amazon Textract and Amazon Comprehend Mona M, Premkumar Rangarajan, Julien Simon

    (ebook) (audiobook) (audiobook) Książka w języku angielskim
    Natural Language Processing with AWS AI Services. Derive strategic insights from unstructured data with Amazon Textract and Amazon Comprehend Mona M, Premkumar Rangarajan, Julien Simon - okladka książki

    Natural Language Processing with AWS AI Services. Derive strategic insights from unstructured data with Amazon Textract and Amazon Comprehend Mona M, Premkumar Rangarajan, Julien Simon - okladka książki

    Natural Language Processing with AWS AI Services. Derive strategic insights from unstructured data with Amazon Textract and Amazon Comprehend Mona M, Premkumar Rangarajan, Julien Simon - audiobook MP3

    Natural Language Processing with AWS AI Services. Derive strategic insights from unstructured data with Amazon Textract and Amazon Comprehend Mona M, Premkumar Rangarajan, Julien Simon - audiobook CD

    Autorzy:
    Mona M, Premkumar Rangarajan, Julien Simon
    Wydawnictwo:
    Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
    Ocena:
    Bądź pierwszym, który oceni tę książkę
    Stron:
    508
    Dostępne formaty:
         PDF
         ePub
         Mobi
    Natural language processing (NLP) uses machine learning to extract information from unstructured data. This book will help you to move quickly from business questions to high-performance models in production.
    To start with, you'll understand the importance of NLP in today’s business applications and learn the features of Amazon Comprehend and Amazon Textract to build NLP models using Python and Jupyter Notebooks. The book then shows you how to integrate AI in applications for accelerating business outcomes with just a few lines of code. Throughout the book, you'll cover use cases such as smart text search, setting up compliance and controls when processing confidential documents, real-time text analytics, and much more to understand various NLP scenarios. You'll deploy and monitor scalable NLP models in production for real-time and batch requirements. As you advance, you'll explore strategies for including humans in the loop for different purposes in a document processing workflow. Moreover, you'll learn best practices for auto-scaling your NLP inference for enterprise traffic.
    Whether you're new to ML or an experienced practitioner, by the end of this NLP book, you'll have the confidence to use AWS AI services to build powerful NLP applications.

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    O autorach książki

    Mona M is a senior AI/ML specialist solutions architect at AWS. She is a highly skilled IT professional, with more than 10 years' experience in software design, development, and integration across diverse work environments. As an AWS solutions architect, her role is to ensure customer success in building applications and services on the AWS platform. She is responsible for crafting a highly scalable, flexible, and resilient cloud architecture that addresses customer business problems. She has published multiple blogs on AI and NLP on the AWS AI channel along with research papers on AI-powered search solutions.
    Premkumar Rangarajan is an enterprise solutions architect, specializing in AI/ML at Amazon Web Services. He has 25 years of experience in the IT industry in a variety of roles, including delivery lead, integration specialist, and enterprise architect. He has significant architecture and management experience in delivering large-scale programs across various industries and platforms. He is passionate about helping customers solve ML and AI problems.
    Julien Simon is a Principal Developer Advocate for AI & Machine Learning at Amazon Web Services. He focuses on helping developers and enterprises bring their ideas to life. He frequently speaks at conferences, blogs on the AWS Blog and on Medium, and he also runs an AI/ML podcast.
    Prior to joining AWS, Julien served for 10 years as CTO/VP Engineering in top-tier web startups where he led large Software and Ops teams in charge of thousands of servers worldwide. In the process, he fought his way through a wide range of technical, business and procurement issues, which helped him gain a deep understanding of physical infrastructure, its limitations and how cloud computing can help.

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