Deep Learning for Natural Language Processing

Humans are good at reading text and understanding it, but deep learning can help computer systems do the same. This book by NLP expert Stephan Raaijmakers explains how to use deep learning methods for natural language processing (NLP) to interpret and use text effectively. It is for people with intermediate Python skills and general knowledge of NLP, and no hands-on experience with Keras or deep learning toolkits is required.

Format: Paperback / softback
Length: 404 pages
Publication date: 06 December 2022
Publisher: Manning Publications

Humans possess remarkable abilities when it comes to reading text, extracting key ideas, summarizing information, forming connections, and engaging in a wide range of tasks that demand comprehension and contextual understanding. In recent years, remarkable advancements in deep learning have opened up a new realm of possibilities, enabling computer systems to attain similar levels of proficiency in these cognitive tasks.

Deep Learning for Natural Language Processing is a comprehensive guide that empowers readers to leverage the power of deep learning techniques in natural language processing (NLP). Authored by NLP expert Stephan Raaijmakers, this insightful book offers a deep dive into the latest state-of-the-art developments in this rapidly evolving field.

The book provides an overview of NLP and deep learning, covering essential concepts such as textual similarity models, deep memory-based NLP, semantic role labeling, and sequential NLP. It is designed for individuals with intermediate Python skills and a general understanding of NLP, with no prior hands-on experience with Keras or deep learning toolkits required.

Natural language processing (NLP) is a multidisciplinary field that focuses on teaching computers to interpret and process human language. In recent years, NLP technology has experienced a remarkable transformation thanks to the application of deep learning, a form of neural network-based machine learning. Deep learning algorithms have the ability to learn complex patterns and relationships in text, making them highly effective in tasks such as sentiment analysis, language translation, and question answering.

Stephan Raaijmakers, a senior scientist at TNO and a Ph.D. in machine learning and text analytics, is the technical coordinator of two significant European Union-funded research projects related to security. He has a wealth of experience in the field and is currently anticipating an endowed professorship in deep learning and NLP at a prominent Dutch university.

With its comprehensive coverage, practical examples, and expert insights, Deep Learning for Natural Language Processing is an invaluable resource for anyone seeking to harness the power of deep learning in NLP. Whether you are a data scientist, researcher, or simply interested in exploring the latest advancements in this field, this book will provide you with the knowledge and tools you need to succeed.

Weight: 548g
Dimension: 188 x 236 x 25 (mm)
ISBN-13: 9781617295447