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"The DL-Learner software learns concepts in Description Logics (DLs) from user-provided examples. Equivalently, it can be used to learn classes in OWL ontologies from selected objects. It extends Inductive Logic Programming to Descriptions Logics and the Semantic Web. The goal of DL-Learner is to provide a DL/OWL based machine learning tool to solve supervised learnings tasks and support knowledge engineers in constructing knowledge and learning about the data they created. Read more ..."

"The Apache Mahout™ machine learning library's goal is to build scalable machine learning libraries."

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"DLMA represents the standards-setting representatives of over 530 of the leading digital publishing, educational technology and e-learning organizations worldwide via its stakeholder organizations. Collectively the DLMA stakeholder organizations have over 60 years tenure as successful standards-setting organizations. Our mission is to coordinate metadata standards adoption and development in support of digital learning and education across the educational technology, publishing, web and library communities via existing metadata frameworks while encouraging innovation and the evolution to next generation metadata frameworks."

The Apache OpenNLP library is a machine learning based toolkit for the processing of natural language text. It supports the most common NLP tasks, such as tokenization, sentence segmentation, part-of-speech tagging, named entity extraction, chunking, parsing, and coreference resolution. These tasks are usually required to build more advanced text processing services. OpenNLP also includes maximum entropy and perceptron based machine learning.

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"is a framework for supervised Machine Learning in OWL, RDF and Description Logics."

"TensorFlow Quantum is a library for hybrid quantum-classical machine learning. TensorFlow Quantum (TFQ) is a quantum machine learning library for rapid prototyping of hybrid quantum-classical ML models. Research in quantum algorithms and applications can leverage Google's quantum computing frameworks, all from within TensorFlow."

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The Apache OpenNLP library is a machine learning based toolkit for the processing of natural language text.

Create autonomous systems including interactive physical robots and synthetic characters in virtual worlds that learn to communicate in human-like ways; (2) Understand how children learn to communicate through longitudinal in vivo observation and analysis; (3) Develop tools for visualizing, searching, and analyzing large corpora (e.g., video) using task-dependent semantic models.

"Skymind is the company behind Deeplearning4j, the only commercial-grade, open-source, distributed deep-learning library written for Java and Scala. Integrated with Hadoop and Spark, DL4J is specifically designed to run in business environments on distributed GPUs and CPUs."

"machine learning and natural language processing, especially for large data sets by Joseph Turian and colleagues"

The DARPA PAL program (the Personalized Assistant that Learns) focused on improving the way that computers support humans through the use of cognitive systems-that is, systems that reason, learn from experience, and accept guidance in order to provide effective, personalized assistance.

The first Semantic Engine that learns Add a semantic flavor to your apps. With  Meaningtool you can create your own   Semantic Trees and let its intelligence    learn new concepts to filter and categorize     websites, text and users in any language!

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"The Open Relevance Project (ORP) is a small Apache LuceneTM sub-project aimed at making materials for doing relevance testing for Information Retrieval (IR), Machine Learning and Natural Language Processing (NLP) into open source."

Intelligent Network of Querying and Learning Engines