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    Deep Learning for Natural Language Processing. Solve your natural language processing problems with smart deep neural networks Karthiek Reddy Bokka, Shubhangi Hora, Tanuj Jain, Monicah Wambugu

    (ebook) (audiobook) (audiobook) Książka w języku 1
    Deep Learning for Natural Language Processing. Solve your natural language processing problems with smart deep neural networks Karthiek Reddy Bokka, Shubhangi Hora, Tanuj Jain, Monicah Wambugu - okladka książki

    Deep Learning for Natural Language Processing. Solve your natural language processing problems with smart deep neural networks Karthiek Reddy Bokka, Shubhangi Hora, Tanuj Jain, Monicah Wambugu - okladka książki

    Deep Learning for Natural Language Processing. Solve your natural language processing problems with smart deep neural networks Karthiek Reddy Bokka, Shubhangi Hora, Tanuj Jain, Monicah Wambugu - audiobook MP3

    Deep Learning for Natural Language Processing. Solve your natural language processing problems with smart deep neural networks Karthiek Reddy Bokka, Shubhangi Hora, Tanuj Jain, Monicah Wambugu - audiobook CD

    Autorzy:
    Karthiek Reddy Bokka, Shubhangi Hora, Tanuj Jain, Monicah Wambugu
    Wydawnictwo:
    Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
    Ocena:
    Bądź pierwszym, który oceni tę książkę
    Stron:
    372
    Dostępne formaty:
         PDF
         ePub
         Mobi
    Applying deep learning approaches to various NLP tasks can take your computational algorithms to a completely new level in terms of speed and accuracy. Deep Learning for Natural Language Processing starts by highlighting the basic building blocks of the natural language processing domain.

    The book goes on to introduce the problems that you can solve using state-of-the-art neural network models. After this, delving into the various neural network architectures and their specific areas of application will help you to understand how to select the best model to suit your needs. As you advance through this deep learning book, you’ll study convolutional, recurrent, and recursive neural networks, in addition to covering long short-term memory networks (LSTM). Understanding these networks will help you to implement their models using Keras. In later chapters, you will be able to develop a trigger word detection application using NLP techniques such as attention model and beam search.

    By the end of this book, you will not only have sound knowledge of natural language processing, but also be able to select the best text preprocessing and neural network models to solve a number of NLP issues.

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    O autorach książki

    Karthiek Reddy Bokka is a Speech and Audio Machine Learning Engineer graduated from University of Southern California and currently working for Biamp Systems in Portland. His interests include Deep Learning, Digital Signal and Audio Processing, Natural Language Processing, Computer Vision. He has experience in designing, building, deploying applications with Artificial Intelligence to solve real-world problems with varied forms of practical data, including Image, Speech, Music, unstructured raw data etc.
    Shubhangi Hora is a data scientist, Python developer, and published writer. With a background in computer science and psychology, she is particularly passionate about healthcare-related AI, including mental health. Shubhangi is also a trained musician.
    Tanuj Jain is a data scientist working at a Germany-based company. He has a masters degree in electrical engineering with a focus on statistical pattern recognition. He has been developing deep learning models and putting them in production for commercial use at his current job. Natural language processing is a special interest area for him and he has applied his know-how to classification and sentiment rating tasks.
    Monicah Wambugu is the lead Data Scientist at Loanbee, a financial technology company that offers micro-loans by leveraging on data, machine learning and analytics to perform alternative credit scoring. She is a graduate student at the School of Information at UC Berkeley Masters in Information Management and Systems. Monicah is particularly interested in how data science and machine learning can be used to design products and applications that respond to the behavioral and socio-economic needs of target audiences.

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