Search Results for "project-nightwing" - Page 2
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Showing 801 open source projects for "project-nightwing"
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ArviZ.jl
Exploratory analysis of Bayesian models with Julia
ArviZ.jl (pronounced "AR-vees") is a Julia package for exploratory analysis of Bayesian models. It includes functions for posterior analysis, model checking, comparison and diagnostics. -
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CompatHelper.jl
Automatically update the [compat] entries for your Julia dependencies
CompatHelper.jl is a Julia package which keeps your Project.toml [compat] entries up to date. -
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FFTW.jl
Julia bindings to the FFTW library for fast Fourier transforms
This package provides Julia bindings to the FFTW library for fast Fourier transforms (FFTs), as well as functionality useful for signal processing. These functions were formerly a part of Base Julia. Users with a build of Julia based on Intel's Math Kernel Library (MKL) can use MKL for FFTs by setting a preference in their top-level project by either using the FFTW.set_provider!() method, or by directly setting the preference using Preferences.jl. Note that this choice will be recorded... -
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SQLBucket
Lightweight library to write, orchestrate and test your SQL ETL
SQLBucket is a lightweight framework to help write, orchestrate and validate SQL data pipelines. It gives the possibility to set variables and introduces some control flow using the fantastic Jinja2 library. It also implements a very simplistic unit and integration test framework where you can validate the results of your ETL in the form of SQL checks. With SQLBucket, you can apply TDD principles when writing data pipelines. To start working, you need to instantiate your SQLBucket core... -
ConnectWise SIEM (formerly Perch) offers threat detection and response backed by an in-house Security Operations Center (SOC). Defend against business email compromise, account takeovers, and see beyond your network traffic. Our team of threat analysts does all the tedium for you, eliminating the noise and sending only identified and verified treats to action on. Built with multi-tenancy, ConnectWise SIEM helps you keep clients safe with the best threat intel on the market.
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CleanVision
Automatically find issues in image datasets
CleanVision automatically detects potential issues in image datasets like images that are: blurry, under/over-exposed, (near) duplicates, etc. This data-centric AI package is a quick first step for any computer vision project to find problems in the dataset, which you want to address before applying machine learning. CleanVision is super simple -- run the same couple lines of Python code to audit any image dataset! The quality of machine learning models hinges on the quality of the data used... -
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Elementary
Open-source data observability for analytics engineers
Elementary is an open-source data observability solution for data & analytics engineers. Monitor your dbt project and data in minutes, and be the first to know of data issues. Gain immediate visibility, detect data issues, send actionable alerts, and understand the impact and root cause. Generate a data observability report, host it or share with your team. Monitoring of data quality metrics, freshness, volume and schema changes, including anomaly detection. Elementary data monitors... -
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Amazon Kinesis Flink Connectors
Contains various Apache Flink connectors to connect to AWS data
This library contains various Apache Flink connectors to connect to AWS data sources and sinks. This repository contains various Apache Flink connectors to connect to AWS Kinesis data sources and sinks. Flink maintain backwards compatibility for the Sink interface used by the Firehose Producer. This project is compatible with Flink 1.x, there is no guarantee it will support Flink 2.x should it release in the future. An Apache Flink application is a Java or Scala application that is created... -
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Cookiecutter Data Science
Project structure for doing and sharing data science work
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work. When we think about data analysis, we often think just about the resulting reports, insights, or visualizations. While these end products are generally the main event, it's easy to focus on making the products look nice and ignore the quality of the code that generates them. Because these end products are created programmatically, code quality is still important! And we're not talking... -
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Gource
Software version control visualization
Software projects are displayed by Gource as an animated tree with the root directory of the project at its centre. Directories appear as branches with files as leaves. Developers can be seen working on the tree at the times they contributed to the project. Gource includes built-in log generation support for Git, Mercurial, Bazaar and SVN. Gource can also parse logs produced by several third party tools for CVS repositories. Gource is a visualization tool for source control repositories... -
PMG is a low-code software platform that allows users to configure automation solutions and business applications to drive digital transformation initiatives. From streamlining business processes through automation, to integrating existing systems and filling in point solution functionality gaps, to delivering a collaborative workspace and unified user experience – PMG’s low-code platform does it all without coding. Business users as well as IT resources are empowered to configure, deploy, and maintain solutions that meet their company’s specific needs.
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kotlin-math
Set of Kotlin APIs to make graphics math easier to write.
Set of Kotlin APIs to make graphics math easier to write. These APIs are mostly modeled after GLSL (OpenGL Shading Language) to make porting code to and from shaders easier. The various types offered by this library are only meant to be value types. Most APIs are therefore exposed as top-level functions and not as methods. -
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Braket.jl
Experimental Julia implementation of the Amazon Braket SDK
Braket.jl is not an officially supported AWS product. This package is a Julia implementation of the Amazon Braket SDK allowing customers to access Quantum Hardware and Simulators. This is experimental software, and support may be discontinued in the future. For a fully supported SDK, please use the Python SDK. We may change, remove, or deprecate parts of the API when making new releases. Please review the CHANGELOG for information about changes in each release. -
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AbstractAlgebra.jl
Generic abstract algebra functionality in pure Julia
AbstractAlgebra is a pure Julia package for computational abstract algebra. It grew out of the Nemo project and provides all of the abstract types and generic implementations that Nemo relies on. It was originally developed by William Hart, Tommy Hofmann, Fredrik Johansson and Claus Fieker with contributions from others. Current maintainers are Claus Fieker, Tommy Hofmann and Max Horn. -
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MethodOfLines.jl
Automatic Finite Difference PDE solving with Julia SciML
MethodOfLines.jl is a Julia package for automated finite difference discretization of symbolically defined PDEs in N dimensions. It uses symbolic expressions for systems of partial differential equations as defined with ModelingToolkit.jl, and Interval from DomainSets.jl to define the space(time) over which the simulation runs. This project is under active development, therefore the interface is subject to change. The docs will be updated to reflect any changes, please check back for current... -
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FastAI.jl
Repository of best practices for deep learning in Julia
FastAI.jl is a Julia library for training state-of-the-art deep learning models. From loading datasets and creating data preprocessing pipelines to training, FastAI.jl takes the boilerplate out of deep learning projects. It equips you with reusable components for every part of your project while remaining customizable at every layer. FastAI.jl comes with support for common computer vision and tabular data learning tasks, with more to come. -
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DynamicalSystems.jl
Award winning software library for nonlinear dynamics timeseries
DynamicalSystems.jl is an award-winning Julia software library for nonlinear dynamics and nonlinear time series analysis. To install DynamicalSystems.jl, run import Pkg; Pkg.add("DynamicalSystems"). To learn how to use it and see its contents visit the documentation, which you can either find online or build locally by running the docs/make.jl file. DynamicalSystems.jl is part of JuliaDynamics, an organization dedicated to creating high-quality scientific software. All implemented algorithms... -
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re_data
re_data - fix data issues before your users & CEO would discover them
re_data is an open-source data reliability framework for the modern data stack. Currently, re_data focuses on observing the dbt project (together with underlying data warehouse - Postgres, BigQuery, Snowflake, Redshift). Gather all relevant outputs about your data in one place using our cloud. Invite your team and debug it easily from there. Go back in time, and see your past metadata. Set up Slack notifications to always know when a new report is produced or an existing one got updated. -
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Pimcore
Open Source Data & Experience Management Platform
No matter if you're dealing with unstructured web documents or structured data for MDM/PIM, you define the UI design (web documents by a template and structured data with an intuitive graphical editor), Pimcore knows how to persist the data efficiently and optimized for fast access. Due to the framework approach, Pimcore is very flexible and adapts perfectly to your needs. Built on top of the well-known Symfony Framework you have a solid and modern foundation for your project. Benefit from all... -
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nb-clean
Clean Jupyter notebooks of outputs, metadata, and empty cells
... can also be used as a pre-commit hook. You may prefer this to the Git filter if your project already uses the pre-commit framework. Note that the Git filter and pre-commit hook work differently, with different effects on your working directory. The pre-commit hook operates on the notebook on disk, cleaning the copy in your working directory. The Git filter cleans notebooks as they are added to the index, leaving the copy in your working directory dirty. -
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dbt-re-data
re_data - fix data issues before your users & CEO would discover them
re_data is an open-source data reliability framework for the modern data stack. Currently, re_data focuses on observing the dbt project (together with underlaying data warehouse - Postgres, BigQuery, Snowflake, Redshift). Data transformations in re_data are implemented and exposed as models & macros in this dbt package. Gather all relevant outputs about your data in one place using our cloud. Invite your team and debug it easily from there. Go back in time, and see your past metadata. Set up... -
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DataQualityDashboard
A tool to help improve data quality standards in data science
The goal of the Data Quality Dashboard (DQD) project is to design and develop an open-source tool to expose and evaluate observational data quality. This package will run a series of data quality checks against an OMOP CDM instance (currently supports v5.4, v5.3 and v5.2). It systematically runs the checks, evaluates the checks against some pre-specified threshold, and then communicates what was done in a transparent and easily understandable way. The quality checks were organized according... -
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Feathr
A scalable, unified data and AI engineering platform for enterprise
Feathr is a data and AI engineering platform that is widely used in production at LinkedIn for many years and was open sourced in 2022. It is currently a project under LF AI & Data Foundation. Define data and feature transformations based on raw data sources (batch and streaming) using Pythonic APIs. Register transformations by names and get transformed data(features) for various use cases including AI modeling, compliance, go-to-market and more. Share transformations and data(features) across... -
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Automated Tool for Optimized Modelling
Automated Tool for Optimized Modelling
During the exploration phase of a machine learning project, a data scientist tries to find the optimal pipeline for his specific use case. This usually involves applying standard data cleaning steps, creating or selecting useful features, trying out different models, etc. Testing multiple pipelines requires many lines of code, and writing it all in the same notebook often makes it long and cluttered. On the other hand, using multiple notebooks makes it harder to compare the results and to keep... -
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SDGym
Benchmarking synthetic data generation methods
... the SDV project, or input your own data. Choose from any of the SDV synthesizers and baselines. Or write your own custom machine learning model. In addition to performance and memory usage, you can also measure synthetic data quality and privacy through a variety of metrics. Install SDGym using pip or conda. We recommend using a virtual environment to avoid conflicts with other software on your device. -
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Wooey
A Django app that creates automatic web UIs for Python scripts
Wooey is a simple web interface to run command line Python scripts. Think of it as an easy way to get your scripts up on the web for routine data analysis, file processing, or anything else. The project was inspired by how simply and powerfully sandman could expose users to a database and by how Gooey turns ArgumentParser-based command-line scripts into WxWidgets GUIs. Originally two separate projects (Django-based djangui by Chris Mitchell and Flask-based Wooey by Martin Fitzpatrick) it has... -
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deck.gl
WebGL2 powered visualization framework
... of the box. Deck.gl is designed to be highly customizable. All layers come with flexible APIs to allow programmatic control of each aspect of the rendering. All core classes such are easily extendable by the users to address custom use cases. deck.gl is part of vis.gl, an OpenJS Foundation project. Read the contribution guidelines if you are interested in contributing.
