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Natural Language Annotation for Machine Learning
Natural Language Annotation for Machine Learning
This book is intended as a resource for people who are interested in using computers to help process natural language. A natural language refers to any language spoken by humans, either currently (e.g., English, Chinese, Spanish) or in the past (e.g., Latin, ancient Greek, Sanskrit). Annotation refers to the process...
Methods for Mining and Summarizing Text Conversations (Synthesis Lecture on Data Management)
Methods for Mining and Summarizing Text Conversations (Synthesis Lecture on Data Management)

Before the invention of the Internet and the creation of the Web, the vast majority of human conversations were in spoken form, with the only notable, but extremely limited, exception being epistolary exchanges. Some important spoken conversations, such as criminal trials and political debates (e.g., Hansard, the transcripts of...

Applied Natural Language Processing with Python: Implementing Machine Learning and Deep Learning Algorithms for Natural Language Processing
Applied Natural Language Processing with Python: Implementing Machine Learning and Deep Learning Algorithms for Natural Language Processing
Learn to harness the power of AI for natural language processing, performing tasks such as spell check, text summarization, document classification, and natural language generation. Along the way, you will learn the skills to implement these methods in larger infrastructures to replace existing code or create new...
Intelligence in Communication Systems: IFIP International Conference, INTELLCOMM 2004
Intelligence in Communication Systems: IFIP International Conference, INTELLCOMM 2004

The 2004 IFIP International Conference on Intelligence in Communication Systems (INTELLCOMM 2004), held in Bangkok, Thailand, 23–26 November 2004, was the successor and an expansion of SMARTNET, a series of annual conferences on intelligence in networks held during 1995–2003 under the auspices of IFIP TC6’s Working Group...

Machine Translation: Its Scope and Limits
Machine Translation: Its Scope and Limits
Machine Translation (MT) is both an engineering technology and a measure of all things to do with languages and computers—whenever a new theory of language or linguistics is offered, an important criteria for its success is whether or not it will improve machine translation.

This book presents a history of machine translation (MT) from...

Text Mining for Biology And Biomedicine
Text Mining for Biology And Biomedicine
Univ. of Manchester, UK. Text provides bioinformatic practitioners with full range of text mining techniques to help address challenges in mining biology and biomedical texts. Includes methods of natural language processing (NLP) and their application in the biological domain; various lexical, terminological, and ontological resources; and...
Computational Approaches to Morphology and Syntax (Oxford Surveys in Syntax & Morphology)
Computational Approaches to Morphology and Syntax (Oxford Surveys in Syntax & Morphology)
"This book should undoubtedly be of great interest to students and researchers of morphology, syntax, computational linguistics, and natural language processing. The book provides an excellent systematics overivew of the current state-of-the-art of the field. The book includes extensive descriptions of the formal characterization of...
Computing Attitude and Affect in Text: Theory and Applications (The Information Retrieval Series)
Computing Attitude and Affect in Text: Theory and Applications (The Information Retrieval Series)
Human Language Technology (HLT) and Natural Language Processing (NLP) systems have typically focused on the "factual" aspect of content analysis. Other aspects, including pragmatics, opinion, and style, have received much less attention. However, to achieve an adequate understanding of a text, these aspects cannot be ignored....
Artificial Intelligence for Big Data: Complete guide to automating Big Data solutions using Artificial Intelligence techniques
Artificial Intelligence for Big Data: Complete guide to automating Big Data solutions using Artificial Intelligence techniques

Build next-generation artificial intelligence systems with Java

Key Features

  • Implement AI techniques to build smart applications using Deeplearning4j
  • Perform big data analytics to derive quality insights using Spark MLlib
  • Create self-learning systems using...
Machine Learning with AWS: Explore the power of cloud services for your machine learning and artificial intelligence projects
Machine Learning with AWS: Explore the power of cloud services for your machine learning and artificial intelligence projects

Use artificial intelligence and machine learning on AWS to create engaging applications

Key Features

  • Explore popular AI and ML services with their underlying algorithms
  • Use the AWS environment to manage your AI workflow
  • Reinforce key concepts with hands-on...
Java Deep Learning Projects: Implement 10 real-world deep learning applications using Deeplearning4j and open source APIs
Java Deep Learning Projects: Implement 10 real-world deep learning applications using Deeplearning4j and open source APIs

Build and deploy powerful neural network models using the latest Java deep learning libraries

Key Features

  • Understand DL with Java by implementing real-world projects
  • Master implementations of various ANN models and build your own DL systems
  • Develop...
Scala Machine Learning Projects: Build real-world machine learning and deep learning projects with Scala
Scala Machine Learning Projects: Build real-world machine learning and deep learning projects with Scala

Powerful smart applications using deep learning algorithms to dominate numerical computing, deep learning, and functional programming.

Key Features

  • Explore machine learning techniques with prominent open source Scala libraries such as Spark ML, H2O, MXNet, Zeppelin, and DeepLearning4j
  • ...
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