Deep Learning for NLP and Speech Recognition

Engelstalig

Uday Kamath, John Liu, James Whitaker

Beoordeel dit boek

Deep Learning for NLP and Speech Recognition - Uday Kamath, John Liu, James Whitaker 1

Deep Learning for NLP and Speech Recognition - Uday Kamath, John Liu, James Whitaker 2

Paperback

Nieuw vanaf 85,95

Koop Tweedehands

Niet tweedehands beschikbaar.

Koop NieuwWeb only

Centraal Magazijn

Adviesprijs 90,95 85,95

De 'adviesprijs' is de prijs die door de fabrikant of leverancier wordt aanbevolen. DeSlegte.com toont deze prijs enkel als referentiekader, zodat je het prijsverschil eenvoudig kunt vergelijken.

Levertijd: 6-9 werkdagen

Omschrijving

With the widespread adoption of deep learning, natural language processing (NLP),and speech applications in many areas (including Finance, Healthcare, and Government) there is a growing need for one comprehensive resource that maps deep learning techniques to NLP and speech and provides insights into using the tools and libraries for real-world applications. Deep Learning for NLP and Speech Recognition explains recent deep learning methods applicable to NLP and speech, provides state-of-the-art approaches, and offers real-world case studies with code to provide hands-on experience.

The book is organized into three parts, aligning to different groups of readers and their expertise. The three parts are:

Machine Learning, NLP, and Speech IntroductionThe first part has three chapters that introduce readers to the fields of NLP, speech recognition, deep learning and machine learning with basic theory and hands-on case studies using Python-based tools and libraries. Deep Learning BasicsThe five chapters in the second part introduce deep learning and various topics that are crucial for speech and text processing, including word embeddings, convolutional neural networks, recurrent neural networks and speech recognition basics. Theory, practical tips, state-of-the-art methods, experimentations and analysis in using the methods discussed in theory on real-world tasks. Advanced Deep Learning Techniques for Text and Speech

The third part has five chapters that discuss the latest and cutting-edge research inthe areas of deep learning that intersect with NLP and speech. Topics includingattention mechanisms, memory augmented networks, transfer learning, multi-tasklearning, domain adaptation, reinforcement learning, and end-to-end deep learning forspeech recognition are covered using case studies.