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  • eBook:Deep Learning for NLP and Speech Recognition

    Deep Learning for NLP and Speech Recognition

    Uday Kamath; John Liu; James Whitaker
    978-3-030-14596-5
    2019
    Edition 1
    • A comprehensive resource that builds up from elementary deep learning, text, and speech principles to advanced state-of-the-art neural architectures
    • A ready reference for deep learning techniques applicable to common NLP and speech recognition applications
    • A useful resource on successful architectures and algorithms with essential mathematical insights explained in detail
    • An in-depth reference and comparison of the latest end-to-end neural speech processing approach
    • A panoramic resource on leading edge transfer learning, domain adaptation and deep reinforcement learning architectures for text and speech
    • Practical aspects of using these techniques with tips and tricks essential for real-world applications
    • A hands-on approach to using Python-based deep learning libraries such as Keras, TensorFlow, and PyTorch to apply these techniques in the context of real-world case studies
    • Thirteen case studies with code, data, and configurations across different approaches for NLP and Speech recognition tasks such as Embeddings, Classification, Distributed Representation, Summarization, Machine Translation, Sentiment Analysis, Cross Domain Transfer Learning, Multi-Task NLP, End to End Speech, and Question Answering

    €419

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