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Showing 427 open source projects for "git:/git.code.sf.net/p/docfetcher/code"
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Soss
Probabilistic programming via source rewriting
Soss is a library for probabilistic programming. Soss and DynamicPPL are both maturing and becoming more complete, so the above will change over time. It's also worth noting that we (the Turing team and I) hope to move toward a natural way of using these systems together to arrive at the best of both. -
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Augmentor.jl
A fast image augmentation library in Julia for machine learning
...In other words, an augmentation pipeline is little more but a sequence of operations for which the parameters can (but need not) be random variables, as the following code snippet demonstrates. -
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gophernotes
The Go kernel for Jupyter notebooks and nteract
gophernotes is a Go kernel for Jupyter notebooks and nteract. It lets you use Go interactively in a browser-based notebook or desktop app. Use gophernotes to create and share documents that contain live Go code, equations, visualizations and explanatory text. These notebooks, with the live Go code, can then be shared with others via email, Dropbox, GitHub and the Jupyter Notebook Viewer. Go forth and do data science, or anything else interesting, with Go notebooks! This project utilizes a Go interpreter called gomacro under the hood to evaluate Go code interactively. ... -
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OpticSim.jl
Optical Simulation software
OpticSim.jl is a Julia package for geometric optics (ray tracing) simulation and optimization of complex optical systems developed by the Microsoft Research Interactive Media Group and the Microsoft Hardware Architecture Incubation Team (HART). It is designed to allow optical engineers to create optical systems procedurally and then to simulate and optimize them. Unlike Zemax, Code V, or other interactive optical design systems OpticSim.jl has limited support for interactivity, primarily in the tools for visualizing optical systems. A large variety of surface types are supported, and these can be composed into complex 3D objects through the use of constructive solid geometry (CSG). A complete catalog of optical materials is provided through the complementary GlassCat submodule. ... -
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Starlight.jl
A greedy game engine for greedy programmers
...Its primary use case is video games, but the power of Julia, SDL2, Vulkan, and the Bullet Physics SDK can be leveraged to make just about anything you want. With a focus on flexibility and code quality, Starlight aims to be such a framework. It includes a suite of components and integrations that make it particuarly well-suited for video games, so it is not a stretch to call it a "game engine". However, Starlight is most fundamentally a scripting layer for SDL, Vulkan, and Bullet (via the Telescope backend), meaning it can be used for any application that needs high-performance rendering and physics. ... -
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Geodesy.jl
Work with points defined in various coordinate systems
...The primary feature of Geodesy is to define and perform coordinate transformations in a convenient and safe framework, leveraging the CoordinateTransformations package. Transformations are accurate and efficient and implemented in native Julia code (with many functions being ported from Charles Karney's GeographicLib C++ library), and some common geodetic datums are provided for convenience. -
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Nonlinear Dynamics
A concise introduction interlaced with code
This repository holds material related with the textbook Nonlinear Dynamics: A Concise Introduction Interlaced with code, co-authored by George Datseris and Ulrich Parlitz. The textbook will be published by Springer-Nature, in the series Undergraduate Lecture Notes in Physics. -
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Deep Learning course
Slides and Jupyter notebooks for the Deep Learning lectures
Slides and Jupyter notebooks for the Deep Learning lectures at Master Year 2 Data Science from Institut Polytechnique de Paris. This course is being taught at as part of Master Year 2 Data Science IP-Paris. Note: press "P" to display the presenter's notes that include some comments and additional references. This lecture is built and maintained by Olivier Grisel and Charles Ollion. -
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AOFlagger
RFI detector and quality analysis for astronomical radio observations
The AOFlagger is a tool that can find and remove radio-frequency interference (RFI) in radio astronomical observations. The code has been highly optimized for speed and accuracy. It is used by default for the LOFAR radio telescope and thus is in productional stage. The software can run in a fully automated way, but a graphical interface is provided to analyse results and tweak the strategy. The preferred input file format is the Casa Measurement Set (MS) format. -
Windocks - Docker Oracle and SQL Server ContainersWindocks is a leader in cloud native database DevOps, recognized by Gartner as a Cool Vendor, and as an innovator by Bloor research in Test Data Management. Novartis, DriveTime, American Family Insurance, and other enterprises rely on Windocks for on-demand database environments for development, testing, and DevOps. Windocks software is easily downloaded for evaluation on standard Linux and Windows servers, for use on-premises or cloud, and for data delivery of SQL Server, Oracle, PostgreSQL, and MySQL to Docker containers or conventional database instances.
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TSNE-CUDA
GPU Accelerated t-SNE for CUDA with Python bindings
This repo is an optimized CUDA version of FIt-SNE algorithm with associated python modules. We find that our implementation of t-SNE can be up to 1200x faster than Sklearn, or up to 50x faster than Multicore-TSNE when used with the right GPU. You can install binaries with anaconda for CUDA version 10.1 and 10.2 using conda install tsnecuda -c conda-forge. Tsnecuda supports CUDA versions 9.0 and later through source installation, check out the wiki for up to date installation instructions.... -
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AWS Step Functions Data Science SDK
For building machine learning (ML) workflows and pipelines on AWS
...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 example notebooks. These notebooks provide code and descriptions for creating and running workflows in AWS Step Functions Using the AWS Step Functions Data Science SDK. In Amazon SageMaker, example Jupyter notebooks are available in the example notebooks portion of a notebook instance. To run the AWS Step Functions Data Science SDK example notebooks locally, download the sample notebooks and open them in a working Jupyter instance. -
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giza
A scientific plotting library for C/Fortran built on cairo
A 2D scientific plotting library built on cairo. Provides uniform output to pdf, ps, png and X-Windows. Written in C with no dependencies (other than cairo) as a direct replacement for PGPLOT. -
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ReinforcementLearningAnIntroduction.jl
Julia code for the book Reinforcement Learning An Introduction
This project provides the Julia code to generate figures in the book Reinforcement Learning: An Introduction(2nd). One of our main goals is to help users understand the basic concepts of reinforcement learning from an engineer's perspective. Once you have grasped how different components are organized, you're ready to explore a wide variety of modern deep reinforcement learning algorithms in ReinforcementLearningZoo.jl. -
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LogicalSets
Integrated Comprehensive Data Architecture & Methodology
This is an advanced data architecture and methodology. A comprehensive Enterprise Resource Management System. A re-usable database with rules for customization, While being a data driven transaction processing engine, this system has very advanced reporting capabilities. This design eliminates up to 90% of business logic due to the way the data is structured. Uses a concept called Table Sets. Has a compound key that tells the programmer what tableset, which record which applet... -
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RDS - JS - Examples
TypeScript/JavaScript example code using the RDS API
Rich Data Services (or RDS) is a suite of REST APIs designed by Metadata Technology North America (MTNA) to meet various needs for data engineers, managers, custodians, and consumers. RDS provides a range of services including data profiling, mapping, transformation, validation, ingestion, and dissemination. For more information about each of these APIs and how you can incorporate or consume them as part of your work flow please visit the MTNA website. RDS-JS-Examples is... -
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ML workspace
All-in-one web-based IDE specialized for machine learning
...This workspace is the ultimate tool for developers preloaded with a variety of popular data science libraries (e.g., Tensorflow, PyTorch, Keras, Sklearn) and dev tools (e.g., Jupyter, VS Code, Tensorboard) perfectly configured, optimized, and integrated. Usable as remote kernel (Jupyter) or remote machine (VS Code) via SSH. Easy to deploy on Mac, Linux, and Windows via Docker. Jupyter, JupyterLab, and Visual Studio Code web-based IDEs.By default, the workspace container has no resource constraints and can use as much of a given resource as the host’s kernel scheduler allows. -
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stats Koa
Request statistics middleware that stores response times, status code
Request statistics middleware. Request statistics middleware that stores response times, status code counts, etc. -
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Kale
Kubeflow’s superfood for Data Scientists
KALE (Kubeflow Automated pipeLines Engine) is a project that aims at simplifying the Data Science experience of deploying Kubeflow Pipelines workflows. Kubeflow is a great platform for orchestrating complex workflows on top Kubernetes and Kubeflow Pipeline provides the mean to create reusable components that can be executed as part of workflows. The self-service nature of Kubeflow make it extremely appealing for Data Science use, at it provides an easy access to advanced distributed jobs... -
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Quan is designed to model physical quantities in C++ programs. Advantages include automated dimensional analysis checking, automatic unit conversions, self documentation of code.
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Open Grid Analysis and Display System
OpenGrADS provides extensions and interfaces for GrADS.
The Grid Analysis and Display System (GrADS) is an interactive desktop tool for easy access, manipulation, and visualization of earth science data. The OpenGrADS Project seeks to develop advanced interfaces and extensions based on the main GrADS engine. -
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ReplMaker.jl
Simple API for building repl modes in Julia
The idea behind ReplMaker.jl is to make a tool for building (domain-specific) languages in Julia. Suppose you've invented some language called MyLang and you've implemented a parser that turns MyLang code into Julia code which is then supposed to be executed by the Julia runtime. With ReplMaker.jl, you can simply hook your parser into the package and ReplMaker will then create a REPL mode where end users just type MyLang code and have it executed automatically. My hope is for this to be useful to someone who implements a full language or DSL in Julia that uses syntax not supported by Julia's parser and doesn't want to deal with the headache of making their own REPL mode. -
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Data Science Notes
Curated collection of data science learning materials
Data Science Notes is a large, curated collection of data science learning materials, with explanations, code snippets, and structured notes across the typical end-to-end workflow. It spans foundational math and statistics through data wrangling, visualization, machine learning, and practical project organization. The content emphasizes hands-on understanding by pairing narrative notes with runnable examples, making it useful for both self-study and classroom settings. -
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Reproducible-research
A Reproducible Data Analysis Workflow with R Markdown, Git, Make, etc.
...The workflow leverages established tools and practices from software engineering. It combines the benefits of various open-source software tools including R Markdown, Git, Make, and Docker, whose interplay ensures seamless integration of version management, dynamic report generation conforming to various journal styles, and full cross-platform and long-term computational reproducibility. The workflow ensures meeting the primary goals that 1) the reporting of statistical results is consistent with the actual statistical results (dynamic report generation), 2) the analysis exactly reproduces at a later point in time even if the computing platform or software is changed (computational reproducibility), and 3) changes at any time (during development and post-publication) are tracked, tagged, and documented while earlier versions of both data and code remain accessible. -
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OzGIS free open-source mapping system
Analysis and display of Census, business, government attribute data
...The system can be used to to support management decisions associated with, for example, government planning, marketing, sales, site and personnel location, advertising and research. Systems for Windows, Mac and Ubuntu, source code, sample data files and manuals are included. DOWNLOAD to your Downloads directory and unzip to Downloads/OzGIS ; see the Files tab for installation instructions. See the installation manual or "OzGIS Installation" Youtube video for help with getting started. I am unable to show OzGIS to you, so suggest that you search for "OzGIS lloyd" on Youtube for demonstration videos or "OzGIS" on Pinterest for example maps. ... -
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JuliaDB.jl
Parallel analytical database in pure Julia
...JuliaDB provides distributed table and array datastructures with convenient functions to load data from CSV. JuliaDB is Julia all the way down. This means queries can be composed with Julia code that may use a vast ecosystem of packages.
