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
Table of contents (13 chapters)
Introduction
Kamath, Uday (et al.)
Pages 3-38
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Basics of Machine Learning
Kamath, Uday (et al.)
Pages 39-86
Text and Speech Basics
Kamath, Uday (et al.)
Pages 87-138
Basics of Deep Learning
Kamath, Uday (et al.)
Pages 141-201
Distributed Representations
Kamath, Uday (et al.)
Pages 203-261
Convolutional Neural Networks
Kamath, Uday (et al.)
Pages 263-314
Recurrent Neural Networks
Kamath, Uday (et al.)
Pages 315-368
Automatic Speech Recognition
Kamath, Uday (et al.)
Pages 369-404
Attention and Memory Augmented Networks
Kamath, Uday (et al.)
Pages 407-462
Transfer Learning: Scenarios, Self-Taught Learning, and Multitask Learning
Kamath, Uday (et al.)
Pages 463-493
Transfer Learning: Domain Adaptation
Kamath, Uday (et al.)
Pages 495-535
End-to-End Speech Recognition
Kamath, Uday (et al.)
Pages 537-574
Deep Reinforcement Learning for Text and Speech
Kamath, Uday (et al.)
Pages 575-613