Karthiek Reddy Bokka - Deep Learning for Natural Language Processing: Solve your natural language processing problems with smart deep neural networks

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 off 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. 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). In the later chapters, you will be able to develop applications 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 you will also be able to select the best text pre-processing and neural network models to solve a number of NLP issues.

Karthiek Reddy Bokka is a speech and audio machine learning engineer graduate from the University of Southern California and is currently working for Bi-amp Systems in Portland. His interests include deep learning, digital signal and audio processing, natural language processing, and computer vision. He has experience in designing, building, and deploying applications with artificial intelligence to solve real-world problems with varied forms of practical data, including image, speech, music, unstructured raw data, and such.