Search Results for "open java projects" - Page 5
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Showing 208 open source projects for "open java projects"
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PyTorch Book
PyTorch tutorials and fun projects including neural talk
This is the corresponding code for the book "The Deep Learning Framework PyTorch: Getting Started and Practical", but it can also be used as a standalone PyTorch Getting Started Guide and Tutorial. The current version of the code is based on pytorch 1.0.1, if you want to use an older version please git checkout v0.4or git checkout v0.3. Legacy code has better python2/python3 compatibility, CPU/GPU compatibility test. The new version of the code has not been fully tested, it has been tested... -
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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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Caffe Framework
Caffe, a fast open framework for deep learning
Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR) and by community contributors. Yangqing Jia created the project during his PhD at UC Berkeley. Caffe is released under the BSD 2-Clause license. Expressive architecture encourages application and innovation. Models and optimization are defined by configuration without hard-coding. Switch between CPU and GPU by setting a single flag to train on a GPU machine... -
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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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Deep Learning with Keras and Tensorflow
Introduction to Deep Neural Networks with Keras and Tensorflow
Introduction to Deep Neural Networks with Keras and Tensorflow. To date tensorflow comes in two different packages, namely tensorflow and tensorflow-gpu, whether you want to install the framework with CPU-only or GPU support, respectively. NVIDIA Drivers and CuDNN must be installed and configured before hand. Please refer to the official Tensorflow documentation for further details. Since version 0.9 Theano introduced the libgpuarray in the stable release (it was previously only available in... -
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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...
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DSTK - DataScience ToolKit
DSTK - DataScience ToolKit for All of Us
...DSTK is written in C#, Java and Python to interface with R, NLTK, and Weka. It can be expanded with plugins using R Scripts. We have also created plugins for more statistical functions, and Big Data Analytics with Microsoft Azure HDInsights (Spark Server) with Livy. License: R, RStudio, NLTK, SciPy, SKLearn, MatPlotLib, Weka, ... each has their own licenses. -
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Caffe
A fast open framework for deep learning
...Caffe is developed by the Berkeley AI Research (BAIR)/The Berkeley Vision and Learning Center (BVLC) and a great community of contributors that continue to make Caffe state-of-the-art in both code and models. It’s been used in numerous projects, from startup prototypes and academic research projects, to large scale industrial applications. -
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Swift AI
The Swift machine learning library
Swift AI is a high-performance deep learning library written entirely in Swift. We currently offer support for all Apple platforms, with Linux support coming soon. Swift AI includes a collection of common tools used for artificial intelligence and scientific applications. A flexible, fully-connected neural network with support for deep learning. Optimized specifically for Apple hardware, using advanced parallel processing techniques. We've created some example projects to demonstrate the... -
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H2O-3
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning
H2O-3 is an open-source machine learning platform designed to build scalable and distributed machine learning models across large datasets. The system operates as an in-memory computing platform that allows data scientists to train models quickly using distributed resources. It supports many machine learning algorithms including generalized linear models, gradient boosting machines, deep learning networks, and ensemble techniques. -
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All future developments will be implemented in the new MATLAB toolbox SciXMiner, please visit https://sourceforge.net/projects/scixminer/ to download the newest version. The former Matlab toolbox Gait-CAD was designed for the visualization and analysis of time series and features with a special focus to data mining problems including classification, regression, and clustering.
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fantail-mlkit
The fantail machine learning toolkit (Moved)
Moved to https://github.com/quansun/fantail-ml -
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JCLTP
A Java Class Library for Text Processing
JCLTP is a class library designed for processing text. JCLTP is free, open source and developed with the Java programming language. JCLTP is distributed under the GNU license. It incorporates several technologies that enable process information while applying AI techniques, in order to build predictive models for text classification. Through a flexible structure of interfaces and classes, the opportunity to extend, adapt and add functionality JCLTP is provided. -
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BagaturChess
Java Chess Engine
This is UCI Chess Engine writen in Java. Since version 1.4 (inclusive) the project was moved to https://github.com/bagaturchess/Bagatur -
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Mass-based dissimilarity
A data dependent dissimilarity measure based on mass estimation.
This software calculates the mass-based dissimilarity matrix for data mining algorithms relying on a distance measure. References: Overcoming Key Weaknesses of Distance-based Neighbourhood Methods using a Data Dependent Dissimilarity Measure. KDD 2016 http://dx.doi.org/10.1145/2939672.2939779 The source code, presentation slide and poster are attached under "Files". The presentation video in KDD 2016 is published on https://youtu.be/eotD_-SuEoo . Since this software is licensed... -
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jPrediction
Open project ternary classifier of the machine learning
Open project ternary classifier of the machine learning -
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JCLAL
A Java Class Library for Active Learning
JCLAL is a general purpose framework developed in Java for the active learning research area. JCLAL framework is open source software and it is distributed under the GNU general public license. It is constructed with a high-level software environment, with a strong object oriented design and use of design patterns, which allow to the developers reuse, modify and extend the framework. -
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sgmweka
Weka wrapper for the SGM toolkit for text classification and modeling.
...Has lower time complexity of classification than comparable software due to inference based on sparse model representation and use of an inverted index. The provided .zip file is in the Weka package format, giving access to text classification. Other functions are usable through either Java command-line commands or class inclusion into Java projects. -
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Scene is a computer vision framework that performs background subtraction and object tracking, using two traditional algorithms and three more recent algorithms based on neural networks and fuzzy classification rules. For each detected object, Scene sends TUIO messages to one or several client applications. The present release features GPU accelerated versions of all the background subtraction methods and morphological post processing of the object blobs with dilation and erosion filters,...
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jLDADMM
A Java package for the LDA and DMM topic models
The Java package jLDADMM is released to provide alternative choices for topic modeling on normal or short texts. It provides implementations of the Latent Dirichlet Allocation topic model and the one-topic-per-document Dirichlet Multinomial Mixture model (i.e. mixture of unigrams), using collapsed Gibbs sampling. In addition, jLDADMM supplies a document clustering evaluation to compare topic models. See the usage of jLDADMM in its website at http://jldadmm.sourceforge.net/
