Kategoria BISAC: Computers >> Artificial Intelligence - Natural Language Processing

As natural language processing spans many different disciplines, it is sometimes difficult to understand the contributions and the challenges that each of them presents. This book explores the special relationship between natural language processing and cognitive science, and the contribution of computer science to these two fields. It is based on the recent research papers submitted at the international workshops of Natural Language and Cognitive Science (NLPCS) which was launched in 2004 in an effort to bring together natural language researchers, computer scientists, and cognitive and...

This book constitutes the refereed proceedings of the 28^th International Conference on Data Analytics and Management in Data Intensive Domains, DAMDID/RCDL 2016, held in Ershovo, Moscow, Russia, in October 2016.

The 16 revised full papers presented together with one invited talk and two keynote papers were carefully reviewed and selected from 57 submissions. The papers are organized in topical sections on semantic modeling in data intensive domains; knowledge and learning management; text mining; data infrastructures in astrophysics; data analysis; research...

Deep learning has revolutionized a number of applications in artificial intelligence, including speech, vision, natural language, game playing, healthcare, and robotics. In particular, the recent striking success of deep learning in a wide variety of Natural Language Processing (NLP) application areas has been taken as a landmark of deep learning in one of the most important tasks in Artificial Intelligence.

The book presents the state-of-the-art of deep learning research, and its applications in major NLP tasks including speech recognition, lexical analysis, parsing, knowledge...

This book constitutes the proceedings of the 23^rd International Symposium on Foundations of Intelligent Systems, ISMIS 2017, held in Warsaw, Poland, in June 2017. The 56 regular and 15 short papers presented in this volume were carefully reviewed and selected from 118 submissions. The papers include both theoretical and practical aspects of machine learning, data mining methods, deep learning, bioinformatics and health informatics, intelligent information systems, knowledge-based systems, mining temporal, spatial and spatio-temporal data, text and Web mining. In addition, four...

Learn how to solve challenging machine learning problems with Tensorflow, Google's revolutionary new system for deep learning. If you have some background with basic linear algebra and calculus, this practical book shows you how to build--and when to use--deep learning architectures. You'll learn how to design systems capable of detecting objects in images, understanding human speech, analyzing video, and predicting the properties of potential medicines.

TensorFlow for Deep Learning teaches concepts through practical examples and builds understanding of deep learning...