Search Results for "open office java" - Page 2
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Showing 162 open source projects for "open office java"
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AminePlatform
Amine is a Multi-Layer Platform for the dev. of Intelligent Systems
Amine is an Artificial Intelligence Multi-Layer Java Open Source Platform dedicated to the development of various kinds of Intelligent Systems and Agents (Knowledge-Based, Ontology-Based, Conceptual Graph -CG- Based, NLP, Reasoning and Learning, Natural Language Processing, etc.). Ontology, KB can be created and manipulated with various processes. CG theory is used as the main knowledge representation language. -
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KotlinDL
High-level Deep Learning Framework written in Kotlin
KotlinDL is a high-level Deep Learning API written in Kotlin and inspired by Keras. Under the hood, it uses TensorFlow Java API and ONNX Runtime API for Java. KotlinDL offers simple APIs for training deep learning models from scratch, importing existing Keras and ONNX models for inference, and leveraging transfer learning for tailoring existing pre-trained models to your tasks. This project aims to make Deep Learning easier for JVM and Android developers and simplify deploying deep learning... -
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Apache MXNet (incubating)
A flexible and efficient library for deep learning
Apache MXNet is an open source deep learning framework designed for efficient and flexible research prototyping and production. It contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations. On top of this is a graph optimization layer, overall making MXNet highly efficient yet still portable, lightweight and scalable. -
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CodeSearchNet
Datasets, tools, and benchmarks for representation learning of code
...The project was created through collaboration between GitHub and Microsoft Research and aims to support research on semantic code search and program understanding. The dataset contains millions of pairs of source code functions and corresponding documentation comments extracted from open-source repositories. These pairs allow machine learning models to learn relationships between natural language descriptions and programming code. The dataset currently covers several widely used programming languages, including Python, JavaScript, Ruby, Go, Java, and PHP. In addition to the dataset itself, the repository includes baseline models, evaluation tools, and instructions for building code retrieval systems that can map user queries to relevant code snippets. -
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Record matching software
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A Synthetic Data Generator for producing mixed datasets described by relevant, irrelevant, and redundant features.
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BerryNet
Deep learning gateway on Raspberry Pi and other edge devices
This project turns edge devices such as Raspberry Pi into an intelligent gateway with deep learning running on it. No internet connection is required, everything is done locally on the edge device itself. Further, multiple edge devices can create a distributed AIoT network. At DT42, we believe that bringing deep learning to edge devices is the trend towards the future. It not only saves costs of data transmission and storage but also makes devices able to respond according to the events... -
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Ceka
Crowd Environment and its Knowledge Analysis
A knowledge analysis tool for crowdsourcing based on Weka. We also have a Python version of Crowdsourcing Learning: CrowdwiseKit on GitHub (https://github.com/tssai-lab/CrowdwiseKit). -
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exchange-core
Ultra-fast matching engine written in Java based on LMAX Disruptor
Exchange-core is an open-source market exchange core based on LMAX Disruptor, Eclipse Collections (ex. Goldman Sachs GS Collections), Real Logic Agrona, OpenHFT Chronicle-Wire, LZ4 Java, and Adaptive Radix Trees. Designed for high scalability and pauseless 24/7 operation under high-load conditions and providing low-latency responses. Single order book configuration is capable to process 5M operations per second on 10-years old hardware (Intel® Xeon® X5690) with moderate latency degradation. ... -
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ModelDB
Open Source ML Model Versioning, Metadata, and Experiment Management
An open-source system for Machine Learning model versioning, metadata, and experiment management. ModelDB is an open-source system to version machine learning models including their ingredients code, data, config, and environment and to track ML metadata across the model lifecycle. -
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Neuroph is lightweight Java Neural Network Framework which can be used to develop common neural network architectures. Small number of basic classes which correspond to basic NN concepts, and GUI editor makes it easy to learn and use.
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A.I. Stock Trends With WEKA & TA-Lib
A Repository Of The Java Programs Presented in the Videos.
This is the open/public source code repository for the Java programs shown in the YouTube videos - A.I. Stock Trends With WEKA, TA-Lib and more https://www.youtube.com/channel/UCPxmgFZDS7F06UBBxH5b4mg -
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Shogun
Unified and efficient Machine Learning since 1999
Shogun is a unified and efficient Machine Learning since 1999. Shogun is implemented in C++ and offers automatically generated, unified interfaces to Python, Octave, Java / Scala, Ruby, C#, R, Lua. We are currently working on adding more languages including JavaScript, D, and Matlab. -
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Oryx
Lambda architecture on Apache Spark, Apache Kafka for real-time
Oryx 2 is a realization of the lambda architecture built on Apache Spark and Apache Kafka, but with specialization for real-time large-scale machine learning. It is a framework for building applications but also includes packaged, end-to-end applications for collaborative filtering, classification, regression and clustering. The application is written in Java, using Apache Spark, Hadoop, Tomcat, Kafka, Zookeeper and more. Configuration uses a single Typesafe Config config file, wherein... -
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ADL mining framework
A set of applications for the mining of Activities of Daily Living
The recognition of Activities of Daily Living (ADL) has represented one of the most developed research areas in recent years. Its objective is to determine what daily activity is developed by the inhabitants of a smart environment. In this project, an ontology-based framework for the mining of ADL with a generic ontology and a modular architecture is proposed. The framework includes applications to: i) load multiple datasets available in literature, ii) to provide different methods for the... -
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jMIR
Music research software
jMIR is an open-source software suite implemented in Java for use in music information retrieval (MIR) research. It can be used to study music in the form of audio recordings, symbolic encodings and lyrical transcriptions, and can also mine cultural information from the Internet. It also includes tools for managing and profiling large music collections and for checking audio for production errors. jMIR includes software for extracting features, applying machine learning algorithms, applying heuristic error error checkers, mining metadata and analyzing metadata. -
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Easy Machine Learning
Easy Machine Learning is a general-purpose dataflow-based system
Machine learning algorithms have become the key components in many big data applications. However, the full potential of machine learning is still far from being realized because using machine learning algorithms is hard, especially on distributed platforms such as Hadoop and Spark. The key barriers come from not only the implementation of the algorithms themselves but also the processing for applying them to real applications which often involve multiple steps and different algorithms. Our... -
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The Teachingbox uses advanced machine learning techniques to relieve developers from the programming of hand-crafted sophisticated behaviors of autonomous agents (such as robots, game players etc...) In the current status we have implemented a well founded reinforcement learning core in Java with many popular usecases, environments, policies and learners. Obtaining the teachingbox: FOR USERS: If you want to download the latest releases, please visit:...
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DGRLVQ
Dynamic Generalized Relevance Learning Vector Quantization
Some of the usual problems for Learning vector quantization (LVQ) based methods are that one cannot optimally guess about the number of prototypes required for initialization for multimodal data structures i.e.these algorithms are very sensitive to initialization of prototypes and one has to pre define the optimal number of prototypes before running the algorithm. If a prototype, for some reasons, is ‘outside’ the cluster which it should represent and if there are points of a different... -
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This application allow user to predict dissolution profile of solid dispersion systems based on algorithms like symbolic regression, deep neural networks, random forests or generalized boosted models. Those techniques can be combined to create expert system. Application was created as a part of project K/DSC/004290 subsidy for young researchers from Polish Ministry of Higher Education.
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Seldon Server
Machine learning platform and recommendation engine on Kubernetes
Seldon Server is a machine learning platform and recommendation engine built on Kubernetes. Seldon reduces time-to-value so models can get to work faster. Scale with confidence and minimize risk through interpretable results and transparent model performance. Seldon Core focuses purely on deploying a wide range of ML models on Kubernetes, allowing complex runtime serving graphs to be managed in production. Seldon Core is a progression of the goals of the Seldon-Server project but also a more... -
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NNVM
Open deep learning compiler stack for cpu, gpu
The vision of the Apache NNVM Project is to host a diverse community of experts and practitioners in machine learning, compilers, and systems architecture to build an accessible, extensible, and automated open-source framework that optimizes current and emerging machine learning models for any hardware platform. Compilation of deep learning models into minimum deployable modules. Infrastructure to automatically generates and optimize models on more backend with better performance.... -
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Genetic Oversampling Weka Plugin
A Weka Plugin that uses a Genetic Algorithm for Data Oversampling
Weka genetic algorithm filter plugin to generate synthetic instances. This Weka Plugin implementation uses a Genetic Algorithm to create new synthetic instances to solve the imbalanced dataset problem. See my master thesis available for download, for further details. -
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OWL Machine Learning
Machine learning algorithm using OWL
Feature construction and selection are two key factors in the field of Machine Learning (ML). Usually, these are very time-consuming and complex tasks because the features have to be manually crafted. The features are aggregated, combined or split to create features from raw data. This project makes use of ontologies to automatically generate features for the ML algorithms. The features are generated by combining the concepts and relationships that are already in the knowledge base,... -
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The KReator project is a collection of software systems, tools, algorithms and data structures for logic-based knowledge representation. Currently, it includes the software systems KReator and MECore and the library Log4KR: - KReator is an integrated development environment (IDE) for relational probabilistic knowledge representation languages such as Bayesian Logic Programs (BLPs), Markov Logic Networks (MLNs), Relational Maximum Entropy (RME), First-Order Probabilistic...
