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Showing 2489 open source projects for "open source tv"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Stop Storing Third-Party Tokens in Your DatabaseRolling your own OAuth token storage can be a security liability. Token Vault securely stores access and refresh tokens from federated providers and handles exchange and renewal automatically. Connected accounts, refresh exchange, and privileged worker flows included.
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ReservoirComputing.jl
Reservoir computing utilities for scientific machine learning (SciML)
ReservoirComputing.jl provides an efficient, modular and easy-to-use implementation of Reservoir Computing models such as Echo State Networks (ESNs). For information on using this package please refer to the stable documentation. Use the in-development documentation to take a look at not-yet-released features. -
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jill
Command line installer of the Julia Language
On Linux, the best way to install Julia is to use the Generic Linux Binaries. And while all Linux users love manually downloading, unpacking, and linking their software, this script does it for you. -
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luma.gl
High-performance Toolkit for WebGL-based data visualization
luma.gl is a GPU toolkit for the Web-focused primarily on data visualization use cases. luma.gl aims to provide support for GPU programmers that need to work directly with shaders and want a low abstraction API that remains conceptually close to the WebGPU and WebGL APIs. Unlike other common WebGL APIs, the developer can choose to use the parts of luma.gl that support their use case and leave the others behind. While generic enough to be used for general 3D rendering, luma.gl's mandate is... -
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F2
An elegant, interactive and flexible charting library for mobile
F2 is an out-of-the-box visualization engine focused on the mobile terminal, oriented to conventional statistical charts, perfectly supporting the H5 environment and compatible with multiple environments (Node, applet), complete graphics grammar theory, to meet your various visualization needs , professional mobile design guidelines to bring you the best mobile graphics experience. Best practices for moving side charts around design, performance and heterogeneous environments. Based on the... -
Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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FEniCS.jl
A scientific machine learning (SciML) wrapper for the FEniCS
FEniCS.jl is a wrapper for the FEniCS library for finite element discretizations of PDEs. This wrapper includes three parts. Installation and direct access to FEniCS via a Conda installation. Alternatively one may use their current FEniCS installation. A low-level development API and provides some functionality to make directly dealing with the library a little bit easier, but still requires knowledge of FEniCS itself. Interfaces have been provided for the main functions and their... -
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XCharts
A charting and data visualization library for Unity
A charting and data visualization library for Unity. Unity data visualization chart plugin. A UGUIpowerful, easy-to-use, parameter-configurable data visualization chart plug-in. It supports ten built-in charts. A powerful, easy-to-use, configurable charting and data visualization library for Unity. Visual configuration of parameters, real-time preview of effects, and pure code drawing without additional resources. Support ten built-in charts such as line chart, column chart, pie chart, radar... -
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Graffle
Simple GraphQL Client for JavaScript
Graffle is a simple, minimal, and extensible GraphQL client for JavaScript, designed to provide type-safe queries and run in various environments. -
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GDAL.jl
Thin Julia wrapper for GDAL - Geospatial Data Abstraction Library
Julia wrapper for GDAL - Geospatial Data Abstraction Library. This package is a binding to the C API of GDAL/OGR. It provides only a C style usage, where resources must be closed manually, and datasets are pointers. Other packages can build on top of this to provide a more Julian user experience. See for example ArchGDAL.jl. Most users will want to use ArchGDAL.jl instead of using GDAL.jl directly. -
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PartitionedArrays.jl
Vectors and sparse matrices partitioned into pieces
This package provides distributed (a.k.a. partitioned) vectors and sparse matrices in Julia. See the documentation for further details. -
Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
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ScientificTypes.jl
An API for dispatching on the "scientific" type of data
This package makes a distinction between machine type and scientific type of a Julia object. The machine type refers to the Julia type being used to represent the object (for instance, Float64). The scientific type is one of the types defined in ScientificTypesBase.jl reflecting how the object should be interpreted (for instance, Continuous or Multiclass). -
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Tulip.jl
Interior-point solver in pure Julia
Tulip is an open-source interior-point solver for linear optimization, written in pure Julia. It implements the homogeneous primal-dual interior-point algorithm with multiple centrality corrections and therefore handles unbounded and infeasible problems. Tulip’s main feature is that its algorithmic framework is disentangled from linear algebra implementations. -
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Interpolations.jl
Fast, continuous interpolation of discrete datasets in Julia
This package implements a variety of interpolation schemes for the Julia language. It has the goals of ease of use, broad algorithmic support, and exceptional performance. Currently, this package supports B-splines and irregular grids. The API has been designed with the intent to support more options. Initial support for Lanczos interpolation was recently added. Pull requests are more than welcome! It should be noted that the API may continue to evolve over time. -
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EvoTrees.jl
Boosted trees in Julia
A Julia implementation of boosted trees with CPU and GPU support. Efficient histogram-based algorithms with support for multiple loss functions, including various regressions, multi-classification and Gaussian max likelihood. -
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Compose.jl
Declarative vector graphics
Compose is a vector graphics library for Julia. It forms the basis for the statistical graphics system Gadfly. Compose is a declarative vector graphics system written in Julia. It's designed to simplify the creation of complex graphics and serves as the basis of the Gadfly data visualization package. -
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OpenCL.jl
OpenCL Julia bindings
Julia interface for the OpenCL parallel computation API. This package aims to be a complete solution for OpenCL programming in Julia, similar in scope to PyOpenCL for Python. It provides a high level API for OpenCL to make programing hardware accelerators, such as GPUs, FPGAs, and DSPs, as well as multicore CPUs much less onerous. -
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PowerSystems.jl
Data structures in Julia to enable power systems analysis
The PowerSystems.jl package provides a rigorous data model using Julia structures to enable power systems analysis and modeling. In addition to stand-alone system analysis tools and data model building, the PowerSystems.jl package is used as the foundational data container for the PowerSimulations.jl and PowerSimulationsDynamics.jl packages. PowerSystems.jl supports a limited number of data file formats for parsing. -
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CUDA.jl
CUDA programming in Julia
High-performance GPU programming in a high-level language. JuliaGPU is a GitHub organization created to unify the many packages for programming GPUs in Julia. With its high-level syntax and flexible compiler, Julia is well-positioned to productively program hardware accelerators like GPUs without sacrificing performance. The latest development version of CUDA.jl requires Julia 1.8 or higher. If you are using an older version of Julia, you need to use a previous version of CUDA.jl. This will... -
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Java Tablesaw
Java dataframe and visualization library
Tablesaw is a dataframe and visualization library that supports loading, cleaning, transforming, filtering, and summarizing data. If you work with data in Java, it may save you time and effort. Tablesaw also supports descriptive statistics and can be used to prepare data for working with machine learning libraries like Smile, Tribuo, H20.ai, DL4J. Import data from RDBMS, Excel, CSV, TSV, JSON, HTML, or Fixed Width text files, whether they are local or remote (http, S3, etc.) Tablesaw... -
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MathLink.jl
Julia language interface for Mathematica/Wolfram Engine
This package provides access to Mathematica/Wolfram Engine via the MathLink library, now renamed to Wolfram Symbolic Transfer Protocol (WSTP). -
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DiffEqBayes.jl
Extension functionality which uses Stan.jl, DynamicHMC.jl
This repository is a set of extension functionality for estimating the parameters of differential equations using Bayesian methods. It allows the choice of using CmdStan.jl, Turing.jl, DynamicHMC.jl and ApproxBayes.jl to perform a Bayesian estimation of a differential equation problem specified via the DifferentialEquations.jl interface. -
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InvertibleNetworks.jl
A Julia framework for invertible neural networks
Building blocks for invertible neural networks in the Julia programming language. -
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NNlib.jl
Neural Network primitives with multiple backends
This package provides a library of functions useful for neural networks, such as softmax, sigmoid, batched multiplication, convolutions and pooling. Many of these are used by Flux.jl, which loads this package, but they may be used independently. -
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Circuitscape.jl
Algorithms from circuit theory to predict connectivity
Circuitscape is an open-source program that uses circuit theory to model connectivity in heterogeneous landscapes. Its most common applications include modeling the movement and gene flow of plants and animals, as well as identifying areas important for connectivity conservation. The new Circuitscape is built entirely in the Julia language, a new programming language for technical computing. -
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MLJBase.jl
Core functionality for the MLJ machine learning framework
Repository for developers that provides core functionality for the MLJ machine learning framework. MLJ is a Julia framework for combining and tuning machine learning models. This repository provides core functionality for MLJ. -
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JuliaSyntax
A Julia frontend, written in Julia
A Julia compiler frontend, written in Julia. Read the documentation for more information. JuliaSyntax.jl is used as the new default Julia parser in Julia 1.10. It's highly compatible with Julia's older femtoliter-based parser - It parses all of Base, the standard libraries and the General registry. Some minor differences remain where we've decided to fix bugs or strange behaviors in the reference parser. The AST and tree data structures are usable but their APIs will evolve as we try out...
