Search Results for "python-kinterbasdb" - Page 27
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Showing 3282 open source projects for "python-kinterbasdb"
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Grafana: The open and composable observability platformGrafana is the open source analytics & monitoring solution for every database.
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GitHub Actions Version Updater
GitHub Actions Version Updater Updates All GitHub Action Versions
GitHub Actions Version Updater is GitHub Action that is used to update other GitHub Actions in a Repository and create a pull request with the updates. It is an automated dependency updater similar to GitHub's Dependabot, but for GitHub Actions. GitHub Actions Version Updater first goes through all the workflows in a repository and checks for updates for each of the action used in those workflows. If an update is found and if that action is not ignored then the workflows are updated with the... -
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DeepXDE
A library for scientific machine learning & physics-informed learning
DeepXDE is a library for scientific machine learning and physics-informed learning. DeepXDE includes the following algorithms. Physics-informed neural network (PINN). Solving different problems. Solving forward/inverse ordinary/partial differential equations (ODEs/PDEs) [SIAM Rev.] Solving forward/inverse integro-differential equations (IDEs) [SIAM Rev.] fPINN: solving forward/inverse fractional PDEs (fPDEs) [SIAM J. Sci. Comput.] NN-arbitrary polynomial chaos (NN-aPC): solving... -
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SageMaker Hugging Face Inference Toolkit
Library for serving Transformers models on Amazon SageMaker
SageMaker Hugging Face Inference Toolkit is an open-source library for serving Transformers models on Amazon SageMaker. This library provides default pre-processing, predict and postprocessing for certain Transformers models and tasks. It utilizes the SageMaker Inference Toolkit for starting up the model server, which is responsible for handling inference requests. For the Dockerfiles used for building SageMaker Hugging Face Containers, see AWS Deep Learning Containers. The SageMaker Hugging... -
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SageMaker Training Toolkit
Train machine learning models within Docker containers
Train machine learning models within a Docker container using Amazon SageMaker. Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. To train a model, you can include your training script and dependencies in a Docker container that runs your training code. A container provides an effectively isolated environment, ensuring a consistent runtime and... -
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CapRover
Scalable PaaS (automated Docker+nginx), aka Heroku on Steroids
...Deploy apps in your own space (Node js, PHP, Python, Java literally any language!) Simple interface for many docker operations, exposing container ports to host, setting up persistent directories, instance count and etc. Optionally fully customizable Nginx config allowing you to enable HTTP2, specific caching logic, custom SSL certs and etc. -
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txtai
Build AI-powered semantic search applications
txtai executes machine-learning workflows to transform data and build AI-powered semantic search applications. Traditional search systems use keywords to find data. Semantic search applications have an understanding of natural language and identify results that have the same meaning, not necessarily the same keywords. Backed by state-of-the-art machine learning models, data is transformed into vector representations for search (also known as embeddings). Innovation is happening at a rapid... -
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AI4U
Multi-engine plugin to specify agents with reinforcement learning
...Train using multiple concurrent Unity/Godot environment instances. Unity/Godot environment partial control from Python. Wrap Unity/Godot learning environments as a gym. -
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Google Open Source Project Style Guide
Chinese version of Google open source project style guide
Each larger open source project has its own style guide, a series of conventions on how to write code for the project (sometimes more arbitrary). When all the code maintains a consistent style, it is more important when understanding large code bases. easy. The meaning of "style" covers a wide range, from "variables use camelCase" to "never use global variables" to "never use exceptions". The English version of the project maintains the programming style guidelines used in Google. If the... -
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Theia
Cloud & Desktop IDE Platform
Eclipse Theia is an open source extensible platform for developing multi-language Cloud and Desktop IDEs with state-of-the-art web technologies. If you’re not sure if you need a web version or a desktop version or both, Theia is the best solution. It can develop one IDE for both browsers and native desktop applications from a single source. Theia has a highly flexible architecture, allowing extenders and adopters to customize and extend every aspect of it. It supports VS code extensions,... -
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Spotless
Keep your code spotless
Spotless is a tool for formatting and enforcing consistent code style in various languages, streamlining code quality across teams. -
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DevDocs
API Documentation Browser
The devdocs repository powers the DevDocs web application, a fast, offline-friendly documentation browser for many programming languages, libraries, and APIs. It aggregates documentation from multiple sources (e.g., MDN, Python, Ruby, Git, etc.), converts them into a uniform format, and indexes them for instant text searching. The codebase includes a backend that handles ingestion, parsing, and transformation of documentation sources into a static site structure, as well as the client side UI code for browsing, searching, and reading docs in a responsive interface. ... -
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CasADi
CasADi is a symbolic framework for numeric optimization
CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT, etc. It can be used in C++, Python, or Matlab/Octave. CasADi's backbone is a symbolic framework implementing forward and reverse modes of AD on expression graphs to construct gradients, large-and-sparse Jacobians, and Hessians. These expression graphs, encapsulated in Function objects, can be evaluated in a virtual machine or exported to stand-alone C code. Initial value problems in ordinary or differential-algebraic equations (ODE/DAE) can be calculated using explicit or implicit Runge-Kutta methods or interfaces to IDAS/CVODES from the SUNDIALS suite. ... -
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Synapse Machine Learning
Simple and distributed Machine Learning
SynapseML (previously MMLSpark) is an open source library to simplify the creation of scalable machine learning pipelines. SynapseML builds on Apache Spark and SparkML to enable new kinds of machine learning, analytics, and model deployment workflows. SynapseML adds many deep learning and data science tools to the Spark ecosystem, including seamless integration of Spark Machine Learning pipelines with the Open Neural Network Exchange (ONNX), LightGBM, The Cognitive Services, Vowpal Wabbit,... -
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TensorFlow.js
TensorFlow.js is a library for machine learning in JavaScript
TensorFlow.js is a library for machine learning in JavaScript. Develop ML models in JavaScript, and use ML directly in the browser or in Node.js. Use off-the-shelf JavaScript models or convert Python TensorFlow models to run in the browser or under Node.js. Retrain pre-existing ML models using your own data. Build and train models directly in JavaScript using flexible and intuitive APIs. Tensors are the core datastructure of TensorFlow.js They are a generalization of vectors and matrices to potentially higher dimensions. Built on top of TensorFlow.js, the ml5.js library provides access to machine learning algorithms and models in the browser with a concise, approachable API. ... -
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MetricFlow
MetricFlow allows you to define, build, and maintain metrics in code
MetricFlow is an open-source semantic layer engine designed to help organizations define, manage, and query business metrics in a consistent, governed way. It works alongside a data stack—typically built with dbt—and allows you to express metrics as YAML‐based definitions tied to semantic models and dimension tables, rather than embedding logic ad-hoc across many dashboards or scripts. When a user or tool requests a metric (e.g., “monthly revenue by region”), MetricFlow generates optimized,... -
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DocArray
The data structure for multimodal data
DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer multimodal data with a Pythonic API. Door to multimodal world: super-expressive data structure for representing complicated/mixed/nested text, image, video, audio, 3D mesh data. The foundation data structure of Jina, CLIP-as-service, DALL·E Flow, DiscoArt etc. Data... -
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git-delete-merged-branches
Command-line tool to delete merged Git branches
A convenient command-line tool helping you keep repositories clean. Supports deletion of both local and remote branches. Detects multiple forms of de-facto merges (rebase merges, squash merges (needs --effort=3), single or range cherry-picks… leveraging git cherry). Supports workflows with multiple release branches, e.g. only delete branches that have been merged to all of master, dev and staging. Quick interactive configuration. Provider agnostic: Works with GitHub, GitLab, Gitea and any... -
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Django friendly finite state machine
Django friendly finite state machine support
Django-fsm adds simple declarative state management for Django models. If you need parallel task execution, view, and background task code reuse over different flows - check my new project Django-view flow. Instead of adding a state field to a Django model and managing its values by hand, you use FSMField and mark model methods with the transition decorator. These methods could contain side effects of the state change. You may also take a look at the Django-fsm-admin project containing a... -
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Tiny CUDA Neural Networks
Lightning fast C++/CUDA neural network framework
...Lower-end cards must reduce the n_neurons parameter or use the CutlassMLP (better compatibility but slower) instead. tiny-cuda-nn comes with a PyTorch extension that allows using the fast MLPs and input encodings from within a Python context. These bindings can be significantly faster than full Python implementations; in particular for the multiresolution hash encoding. -
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Imagen - Pytorch
Implementation of Imagen, Google's Text-to-Image Neural Network
Implementation of Imagen, Google's Text-to-Image Neural Network that beats DALL-E2, in Pytorch. It is the new SOTA for text-to-image synthesis. Architecturally, it is actually much simpler than DALL-E2. It consists of a cascading DDPM conditioned on text embeddings from a large pre-trained T5 model (attention network). It also contains dynamic clipping for improved classifier-free guidance, noise level conditioning, and a memory-efficient unit design. It appears neither CLIP nor prior... -
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Kornia
Open Source Differentiable Computer Vision Library
Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer vision problems. At its core, the package uses PyTorch as its main backend both for efficiency and to take advantage of the reverse-mode auto-differentiation to define and compute the gradient of complex functions. Inspired by existing packages, this library is composed by a subset of packages containing operators that can be inserted within... -
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Jina
Build cross-modal and multimodal applications on the cloud
Jina is a framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer. Build applications that deliver fresh insights from multiple data types such as text, image, audio, video, 3D mesh, PDF with Jina AI’s DocArray. Polyglot gateway that supports gRPC, Websockets, HTTP,... -
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pmd
An extensible multilanguage static code analyzer
...Additionally, it includes CPD, the copy-paste-detector. CPD finds duplicated code in Java, C, C++, C#, Groovy, PHP, Ruby, Fortran, JavaScript, PLSQL, Apache Velocity, Scala, Objective C, Matlab, Python, Go, Swift and Salesforce.com Apex, and Visualforce. It supports Java, JavaScript, Salesforce.com Apex and Visualforce, Modelica, PLSQL, Apache Velocity, XML, XSL, and Scala. Additionally, it includes CPD, the copy-paste-detector. CPD finds duplicated code in C/C++, C#, Dart, Fortran, Go, Groovy, Java, JavaScript, JSP, Kotlin, Lua, Matlab, Modelica, Objective-C, Perl, PHP, PLSQL, Python, Ruby, Salesforce.com Apex, Scala, Swift, Visualforce and XML. -
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RenderDoc
RenderDoc is a stand-alone graphics debugging tool
RenderDoc is a free MIT licensed stand-alone graphics debugger that allows quick and easy single-frame capture and detailed introspection of any application using Vulkan, D3D11, OpenGL & OpenGL ES or D3D12 across Windows 7 - 10, Linux, Android, Stadia, or Nintendo Switch™. I work on RenderDoc myself and you can always contact me with any problems or comments. I'll respond to you directly and personally, and I'm used to helping people with private or NDA'd projects. RenderDoc is 100% open... -
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Awesome Network Analysis
A curated list of awesome network analysis resources
awesome-network-analysis is a curated list of resources focused on network and graph analysis, including libraries, frameworks, visualization tools, datasets, and academic papers. It covers multiple programming languages and domains like sociology, biology, and computer science. This repository serves as a central reference for researchers, analysts, and developers working with network data.
