Natural language processing (NLP) provides unbounded opportunities for solving interesting problems in artificial intelligence, especially with the availability of flexible deep learning frameworks. With this practical book, developers and data scientists will learn how to implement recently discovered NLP techniques with the open source software library TensorFlow. After providing you with a solid grounding in TensorFlow, you'll learn deep learning algorithms for building applications involving semantic representation of texts via embeddings, sequence modeling using RNNs, LSTMs, and GRUs, and sequence-to-sequence modeling for applications such as Question Answering, Summarization, and Machine Translation. If you have some background in machine learning, this book will help you explore the intersection of NLP and practical aspects of deep learning.

About the Author:

Delip Rao is a machine learning and natural language processing researcher focused on building AI solutions for consumers and businesses. He has worked on NLP and ML research problems involving semi-supervised learning, graph-based ranking, sequence learning, distributed machine learning, and more, and has published several highly cited papers in these areas.

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