Search Results for "java-ml" - Page 3
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Showing 381 open source projects for "java-ml"
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EulerSharp
Euler Yet another proof Engine
EYE [1] is a reasoning engine supporting the Semantic Web layers [2]. It performs controlled chaining and it supports Euler paths [3]. Via N3 [4] it is interoperable with Cwm [5]. [1] http://eulersharp.sourceforge.net/README [2] http://www.w3.org/DesignIssues/diagrams/sweb-stack/2006a [3] http://mathworld.wolfram.com/KoenigsbergBridgeProblem.html [4] http://www.w3.org/TeamSubmission/n3/ [5] http://www.w3.org/2000/10/swap/doc/cwm -
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myScite
The allRound pocket sized CodeEditor.
... - And finally; read & write source code: - [ Syntax highlighted ] - go, vala, pike, swift, flash, ch, rust - [ Calltip assisted ] - c/cpp11, js&jQuery, python, php, ruby, lua, c#, java, perl --Others-- - Restructured config files with inline docs - Scriptable via lua Extension. - Provides theming, a customizeable toolbar, a sidebar with a File Browser and a cleaned up options Menu. --- Summary --- Enjoy your vlc for sourceCode lecture ;) (30Langs) -
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flom
Free Lock Manager
...FLoM supports different types of abstract resources: simple, numeric, set, hierarchical and transactional sequence. libflom, the library shipped with FLoM, allows you to develop your own application using a simple C, C++, Java, Perl, PHP or Python client API. SSL/TLS security for network communication, X.509 certificates for peer to peer mutual authentication. -
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lixa
LIXA, LIbre XA, is a free and open source XA transaction manager
...The client/server architecture of LIXA allows many application containers to share a single LIXA (state) server: this is ideal when horizontal scalability is a must and many identical application containers must refer to a single transactional environment. LIXA can be used with the C, C++, Java, Python and COBOL programming languages. -
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eCxx
A C++ library for AVR and NodeMCU
...However it may still get sporadic commits to the repository. eCxx is a library for AVR and NodeMCU tailored for micro LED displays and lighting effects. eCxx is utilizing Makefile build system. Java and Python based applications/tools are also included to ease the development and debugging process using the host PC. On one side, eCxx supports the original megaAVR series (ATmega328P, ATmega1284P, ATmega2560, ATmega32U4, AT90USB1286, etc.) as well as the new megaAVR 0-Series (ATmega4808, ATmega4809, etc.). On the other side, while eCxx is primarily designed to work in NodeMCU, it should also support other ESP-12 based design as well as ESP-01 based design. ... -
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Empact Foundation Class Library
Cross-platform C++ library for use as a default application framework.
...Features include: * Threading & synchronization * Socket programming: SSL, NanoMsg & ZMQ * File I/O utilities: zlib, ini, yaml * Native Database access: MySQL, SQLite, BerkleyDB, Postgre, REDIS and ODBC * Built-in mini XML parser; optional EXPAT, LIBXML and MSXML support * Network protocol stack: HTTP, FTP, SMTP, POP3, SOAP, XMLRPC * Scripting languages: Perl, Python, JavaScript, VBScript, Java, Lua, TCL, Squirrel * Cloud Computing: AWS * Encryption: OpenSSL * Platforms: Linux/Posix, Windows, Arduino * Over 500+ highly reusable classes. 4000+ fully documented functions. Follow the 'Wiki' link above to explore everything about the framework. -
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PoJamas aims to provide a Python and tools for loading, processing, and producing .cr2, pz3 (crz, pzz) files compatible with the SmithMicro (e-frontier) Poser character animation application. PoJamas is composed of: - Python library - Python Wavefront (.obj) 3D viewer based on GLFW - LibreOffice/Python Application (to ease the library and the viewer usage) As of 2020, the project is ported in Python3 As of 2021 this project proposes a 3D viewer for Wavefront files...
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Muse: Middleware Universal Scripting idE
Automate: WebSphere; WebLogic; JBoss; Glassfish; Tomcat; Linux, WinRM
...Use Python / Jython to automate WebSphere, WebLogic, JBoss, Glassfish and Tomcat Middleware Estates over JMX, both SSL and non-SSL + Linux SSH (agent-less) + WinRM Target all 5 servers, Linux and WinRM from the same workspace. Familiar Eclipse based Jython and Python Development IDE, pre-configured and ready to go. 4-Click Installer. Win x64, Linux WINE x64. Built-In JVM. Java 8/9/10, Amazon Corretto, JETPack13/14/16, IBM SDK Compatible. *** Now with powerful JBoss / GlassFish / Tomcat / Linux Active Auditing Framework. Tomcat / Glassfish 2 Python - Configuration Snapshots *** Infrastructure-as-Code, Code-Writing-Code Designed to Run on JETPack: https://sourceforge.net/projects/jetpack Muse.2025.06.x - Win 10 / Win11 Muse.2023.12.x - Win7 / Win8 / Win 10 / Win11 -
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fastMRI
A large open dataset + tools to speed up MRI scans using ML
fastMRI is a large-scale collaborative research project by Facebook AI Research (FAIR) and NYU Langone Health that explores how deep learning can accelerate magnetic resonance imaging (MRI) acquisition without compromising image quality. By enabling reconstruction of high-fidelity MR images from significantly fewer measurements, fastMRI aims to make MRI scanning faster, cheaper, and more accessible in clinical settings. The repository provides an open-source PyTorch framework with data... -
Leverage AI to Automate Medical CodingAs a healthcare provider, you should be paid promptly for the services you provide to patients. Slow, inefficient, and error-prone manual coding keeps you from the financial peace you deserve. XpertDox’s autonomous coding solution accelerates the revenue cycle so you can focus on providing great healthcare.
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DeepMind Research
Implementations and code to accompany DeepMind publications
This repository collects reference implementations and illustrative code accompanying a wide range of DeepMind publications, making it easier for the research community to reproduce results, inspect algorithms, and build on prior work. The top level organizes many paper-specific directories across domains such as deep reinforcement learning, self-supervised vision, generative modeling, scientific ML, and program synthesis—for example BYOL, Perceiver/Perceiver IO, Enformer for genomics, MeshGraphNets for physics, RL Unplugged, Nowcasting for weather, and more. Each project folder typically includes its own README, scripts, and notebooks so you can run experiments or explore models in isolation, and many link to associated datasets or external environments like DeepMind Lab and StarCraft II. ... -
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The Related Values Processing Framework helps the integration of Process Control Data Historian Systems.
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SMC - The State Machine Compiler
Translates state machine into a target programming language.
SMC takes a state machine stored in a .sm file and generates a State pattern in 14 programming languages. Includes: default transitions, transition args, transition guards, push/pop transitions and Entry/Exit actions. See User Manual for more info. -
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UnionML
Build and deploy machine learning microservices
...Fit the rich ecosystem of tools and frameworks into a common protocol for machine learning. Using industry-standard machine learning methods, implement endpoints for fetching data, training models, serving predictions (and much more) to write a complete ML stack in one place. Data science, ML engineering, and MLOps practitioners can all gather around UnionML apps as a way of defining a single source of truth about your ML system’s behavior. This helps you maintain consistent code across your ML stack, from training to prediction logic. -
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Petastorm
Petastorm library enables single machine or distributed training
Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code. Petastorm is an open-source data access library developed at Uber ATG. This library enables single machine or distributed training and evaluation of deep learning models directly from datasets in Apache Parquet format. Petastorm supports popular Python-based machine learning (ML) frameworks such as Tensorflow, PyTorch, and PySpark. ... -
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Classic HWUT - rename of previous HWUT
Software Unit Tests (Language Independent Approach)
Automation of Unit and System Tests. Tests can be implemented in any language and on many platforms. The flexible approach enables the inclusion of many types of tests, such as memory leak checks (using valgrind), coding rule checks, complexity checks, etc. Tests are run by a simple call to hwut in a base directory of a project. In particular for C, HWUT supports make file generation using 'sos' and 'sols' modes. Remote control-able function stubs may be generated using the 'stub' mode.... -
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ZHSoftware
ZHSoftware
ZH软件&源码库 -
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Hacker Scripts
Based on a true story
...The README explains the origin story and highlights several canonical scripts and provides usage notes such as required environment variables and cron examples for scheduling. Contributors have provided implementations and ports in many languages and folders (shell, Ruby, Python, Node, Perl, PowerShell, Go, Java, etc.), and the project explicitly welcomes pull requests that add additional language implementations. -
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Blankly
Easily build, backtest and deploy your algo in just a few lines
...Models can be instantly backtested, paper traded, sandbox tested and run live by simply changing a single line. We built blankly for every type of quant including training & running ML models in the same environment, cross-exchange/cross-symbol arbitrage, and even long/short positions on stocks (all with built-in WebSockets). Blankly is the first framework to enable developers to backtest, paper trade, and go live across exchanges without modifying a single line of trading logic on stocks, crypto, and forex. Every model needs to figure out how to buy and sell. ... -
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m2cgen
Transform ML models into a native code
m2cgen (Model 2 Code Generator) - is a lightweight library that provides an easy way to transpile trained statistical models into a native code (Python, C, Java, Go, JavaScript, Visual Basic, C#, PowerShell, R, PHP, Dart, Haskell, Ruby, F#, Rust, Elixir). Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies. Some models force input data to be particular type during prediction phase in their native Python libraries. ... -
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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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The Pythonizer
Converts a Java program to the equivalent Python program
An automatic source-code converter (transcompiler) that converts a valid Java program to the equivalent Python program. Uses Python naming conventions and indentation convention. -
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SBW (Systems Biology Workbench)
Framework for Systems Biology
The Systems Biology Workbench(SBW) is a framework for application intercommunications. It uses a broker-based, distributed, message-passing architecture, supports many languages including Java, C++, Perl & Python, and runs under Linux,OSX & Win32. It comes with a large number of modules, encompassing the whole modeling cycle: creating computational models, simulating and analyzing them, visualizing the information, in order to improve the models. All using community standards, such as SED-ML, SBML and MIRIAM. -
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Kikonf is an Universal Administration Platform for MiddleWare Application Servers and related Servers. (Full Support for WebSphere Application Server, WebLogic Server, WebSphere MQ, Tomcat, JBoss, ...)
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AWS Step Functions Data Science SDK
For building machine learning (ML) workflows and pipelines on AWS
The AWS Step Functions Data Science SDK is an open-source library that allows data scientists to easily create workflows that process and publish machine learning models using Amazon SageMaker and AWS Step Functions. You can create machine learning workflows in Python that orchestrate AWS infrastructure at scale, without having to provision and integrate the AWS services separately. The best way to quickly review how the AWS Step Functions Data Science SDK works is to review the related...
