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    Getting Started with Google BERT. Build and train state-of-the-art natural language processing models using BERT Sudharsan Ravichandiran

    (ebook) (audiobook) (audiobook) Książka w języku 1
    Getting Started with Google BERT. Build and train state-of-the-art natural language processing models using BERT Sudharsan Ravichandiran - okladka książki

    Getting Started with Google BERT. Build and train state-of-the-art natural language processing models using BERT Sudharsan Ravichandiran - okladka książki

    Getting Started with Google BERT. Build and train state-of-the-art natural language processing models using BERT Sudharsan Ravichandiran - audiobook MP3

    Getting Started with Google BERT. Build and train state-of-the-art natural language processing models using BERT Sudharsan Ravichandiran - audiobook CD

    Autor:
    Sudharsan Ravichandiran
    Wydawnictwo:
    Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
    Ocena:
    Bądź pierwszym, który oceni tę książkę
    Stron:
    352
    Dostępne formaty:
         PDF
         ePub
         Mobi
    BERT (bidirectional encoder representations from transformer) has revolutionized the world of natural language processing (NLP) with promising results. This book is an introductory guide that will help you get to grips with Google's BERT architecture. With a detailed explanation of the transformer architecture, this book will help you understand how the transformer’s encoder and decoder work.
    You’ll explore the BERT architecture by learning how the BERT model is pre-trained and how to use pre-trained BERT for downstream tasks by fine-tuning it for NLP tasks such as sentiment analysis and text summarization with the Hugging Face transformers library. As you advance, you’ll learn about different variants of BERT such as ALBERT, RoBERTa, and ELECTRA, and look at SpanBERT, which is used for NLP tasks like question answering. You'll also cover simpler and faster BERT variants based on knowledge distillation such as DistilBERT and TinyBERT. The book takes you through MBERT, XLM, and XLM-R in detail and then introduces you to sentence-BERT, which is used for obtaining sentence representation. Finally, you'll discover domain-specific BERT models such as BioBERT and ClinicalBERT, and discover an interesting variant called VideoBERT.
    By the end of this BERT book, you’ll be well-versed with using BERT and its variants for performing practical NLP tasks.

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    O autorze książki

    Sudharsan Ravichandiran is a data scientist and artificial intelligence enthusiast. He holds a Bachelors in Information Technology from Anna University. His area of research focuses on practical implementations of deep learning and reinforcement learning including natural language processing and computer vision. He is an open-source contributor and loves answering questions on Stack Overflow.

    Sudharsan Ravichandiran - pozostałe książki

    Packt Publishing - inne książki

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