Search Results for "as built" - Page 36
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Showing 1298 open source projects for "as built"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Gemini 3 and 200+ AI Models on One PlatformBuild, govern, and optimize agents and models with Gemini Enterprise Agent Platform.
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Jupyter Dash
Dash v2.11+ has Jupyter support built in
Dash 2.11 and later supports running Dash apps in classic Jupyter Notebooks and in JupyterLab without the need to update the code or use the additional JupyterDash library. If you are using an earlier version of Dash, you can run Dash apps in a notebook using JupyterDash. This page documents additional options available when running Dash apps in notebooks as well as troubleshooting information. -
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Scylla
Intelligent proxy pool for collecting and managing public proxies
...It includes a JSON API that allows developers and applications to retrieve proxy information programmatically, making it easier to integrate proxy rotation into scraping tools or automation scripts. Scylla also runs a built-in HTTP forward proxy server that can dynamically select a recently validated proxy whenever a request is made. In addition to the API, the system provides a web-based interface where users can view available proxies and monitor their global distribution through a visual dashboard. It is commonly used by developers who need scalable proxy management when gathering data from the internet or building datasets for machine learning. -
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Userge
Userge, Durable as a Serge
UserGe is a Powerful, Pluggable Telegram UserBot written in Python using Pyrogram by which you can Automate your Telegram account to work as you want. It comes with salient and descriptive features that help you to manage your task with some easy command. -
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SageMaker Scikit-Learn Extension
A library of additional estimators and SageMaker tools based on scikit
...This project contains standalone scikit-learn estimators and additional tools to support SageMaker Autopilot. Many of the additional estimators are based on existing scikit-learn estimators. SageMaker Scikit-Learn Extension is a Python module for machine learning built on top of scikit-learn. In order to use the I/O functionalies in the sagemaker_sklearn_extension.externals module, you will also need to install the mlio version 0.7 package via conda. The mlio package is only available through conda at the moment. You can also install from source by cloning this repository and running a pip install command in the root directory of the repository. ... -
Add Two Lines of Code. Get Full APM.Works out of the box for Rails, Django, Express, Phoenix, and more. Monitoring exceptions and performance in no time.
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Pyicon
Pyicon Is an Python ide Made for experts and beginners.
Pyicon Is an Python ide Made for experts and beginners It uses Python as its general language the ide does not support an built An Built-in CLI You should also save every time before you run so anyways thanks for downloading! -
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DeepStack
The World's Leading Cross Platform AI Engine for Edge Devices
DeepStack is an AI API engine that serves pre-built models and custom models on multiple edge devices locally or on your private cloud. DeepStack runs completely offline and independent of the cloud. You can also install and run DeepStack on any cloud VM with docker installed to serve as your private, state-of-the-art and real-time AI server. -
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Deep Learning Papers Reading Roadmap
Deep Learning papers reading roadmap for anyone who are eager to learn
Deep Learning Papers Reading Roadmap is a widely known curated reading plan for deep learning that helps newcomers and practitioners navigate the vast literature in a structured and intentional way. It is built around several guiding principles: moving from outline to detail, from older foundational papers to state-of-the-art work, and from generic to more specialized areas while keeping a focus on impactful contributions. The roadmap organizes papers into categories such as fundamentals, convolutional networks, sequence models, unsupervised learning, generative models, optimization, and application areas like computer vision or NLP. ... -
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Hugging Face Transformer
CPU/GPU inference server for Hugging Face transformer models
...In that setup, latency is key to providing a good user experience, and relevancy inference is done online for hundreds of snippets per user query. Most tutorials on Transformer deployment in production are built over Pytorch and FastAPI. Both are great tools but not very performant in inference. Then, if you spend some time, you can build something over ONNX Runtime and Triton inference server. You will usually get from 2X to 4X faster inference compared to vanilla Pytorch. It's cool! However, if you want the best in class performances on GPU, there is only a single possible combination: Nvidia TensorRT and Triton. ... -
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GiantMIDI-Piano
Classical piano MIDI dataset
GiantMIDI-Piano is a large-scale symbolic classical piano music dataset built by applying the piano_transcription system on a vast collection of piano performance recordings. The dataset contains thousands of piano works, spanning a large number of composers and styles, with each piece transcribed into high-precision MIDI files capturing note events, pedal usage, velocities, etc. It provides a resource for music information retrieval (MIR), symbolic music modeling, composer classification, music generation, analysis of classical piano repertoire, and data-driven research in musicology or AI-based composition. ... -
Full-stack observability with actually useful AI | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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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... -
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Kaplan Desktop
Free and open-source CAT tool for linguists
A free and open-source computer-assisted translation tool built with Django/Python and Electronjs/Nodejs. For the relevant repositories, please see https://github.com/kaplanPRO kaplanpy currently handles the following doctypes: • .docx • .odp • .ods • .odt • .txt • .xliff (very limited coverage) • .po -
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ClointFusion
Cloint India Pvt. Ltd's (ClointFusion) Pythonic RPA (Automation)
...Once you have successfully completed the self-test, you will receive an email with a self-test report. DOST is an interactive Blockly based no-code BOT Builder platform built and optimized for ClointFusion-based BOT building. We feel that automation is important for people other than programmers. Using DOST, even a common man can create a BOT in minutes. -
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Project Alice
Main repository of Project Alice, contains main unit source code
Project Alice is a smart voice home assistant that is completely modular and extensible. It was first built around Snips therefore runs entirely offline and never sends or shares your voice interactions with anyone, Project Alice guarantees your privacy in your home or wherever you’re using Project Alice. However, as an option, since we've built Project Alice on top of Snips, Project Alice can be configured to use some online alternatives and fall backs (for example, using Amazon or Google’s Text to Speech engines), just like Snips. ... -
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Algobot
Cryptocurrency trading bot with a graphical user interface
Cryptocurrency trading bot that allows users to create strategies and then backtest, optimize, simulate, or run live bots using them. Telegram integration has been added to support easier and remote trading. Please note that Algobot requires TA-LIB. You can view instructions on how to download TA-LIB. For Windows users, it's best to download the .whl package for your Python install and pip install it. For Linux and MacOS users, there's excellent documentation available. Create graphs with... -
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ARPT-Bot
Tool designed to interact with streaming or media-related platforms
ARPT-Bot is an automation tool designed to interact with streaming or media-related platforms, providing automated recording, monitoring, or processing capabilities. It is built to handle repetitive tasks such as tracking live streams, managing content, or executing scripted workflows. The system typically integrates with multimedia tools like FFmpeg to process or capture streams efficiently. It emphasizes automation and reliability, enabling long-running tasks without manual intervention. The architecture allows customization of workflows, making it adaptable for different media-related scenarios. ... -
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Face Mask Detection
Face Mask Detection system based on computer vision and deep learning
Face Mask Detection system based on computer vision and deep learning using OpenCV and Tensorflow/Keras. Face Mask Detection System built with OpenCV, Keras/TensorFlow using Deep Learning and Computer Vision concepts in order to detect face masks in static images as well as in real-time video streams. Amid the ongoing COVID-19 pandemic, there are no efficient face mask detection applications which are now in high demand for transportation means, densely populated areas, residential districts, large-scale manufacturers and other enterprises to ensure safety. ... -
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SVoice (Speech Voice Separation)
We provide a PyTorch implementation of the paper Voice Separation
SVoice is a PyTorch-based implementation of Facebook Research’s study on speaker voice separation as described in the paper “Voice Separation with an Unknown Number of Multiple Speakers.” This project presents a deep learning framework capable of separating mixed audio sequences where several people speak simultaneously, without prior knowledge of how many speakers are present. The model employs gated neural networks with recurrent processing blocks that disentangle voices over multiple... -
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StreamTuner2 ♪♬#
Internet radio directory browser
Streamtuner2 is an internet radio station and video browser. It simply lists stations in categories from different directories. Launches your preferred media apps for playback. It's built in Python now, but retains UI similarity with the original StreamTuner 0.99 -
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MaskFormer
Per-Pixel Classification is Not All You Need for Semantic Segmentation
...Unlike traditional segmentation pipelines that treat these tasks separately, MaskFormer reformulates segmentation as a mask classification problem, enabling a consistent and efficient approach across multiple segmentation domains. Built on top of Detectron2, it supports a wide range of datasets including ADE20K, Cityscapes, COCO-Stuff, and Mapillary Vistas, and provides pretrained baselines for each. The model achieves strong performance and scalability while simplifying training and evaluation workflows. Its successor, Mask2Former, extends the same meta-architecture to achieve state-of-the-art results across all major segmentation benchmarks. ... -
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Nameko
Python framework for building microservices
...Nameko gives you effortless concurrency by yielding workers when they wait for I/O, leaving you free to handle many requests without the worry of threading. Nameko is compatible with almost any protocol, transport or database. Simply use the built-in extensions, build your own or leverage the community. Nameko includes an implementation of RPC over AMQP. It comprises the @rpc entry point, a proxy for services to talk to other services, and a standalone proxy that non-Nameko clients can use to make RPC calls to a cluster. The HTTP entry point is built on top of werkzeug, and supports all the standard HTTP methods (GET/POST/DELETE/PUT etc). -
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What is DracOS GNU/Linux Remastered ? DracOS GNU/Linux Remastered ( https://github.com/dracos-linux ) is the Linux operating system from Indonesia , open source is built based on Debian live project under the protection of the GNU General Public License v3.0. This operating system is one variant of Linux distributions, which is used to perform security testing (penetration testing). Dracos linux in Arm by hundreds hydraulic pentest, forensics and reverse engineering. Use a GUI-based tools-tools the software using the CLI (command line interface) and GUI (graphical user interface) to perform its operations. ...
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Automation Orchestrator
Automation Orchestrator application to orchestrate digital processes
...The Automation Orchestrator is tested with and supports Nintex RPA version = 15.1. As described on the official Django project site, it "is a high-level Python Web framework that encourages rapid development and clean, pragmatic design. Built by experienced developers, it takes care of much of the hassle of Web development, so you can focus on writing your app without needing to reinvent the wheel. It’s free and open source." The purpose of the Automation Orchestrator is to offer a well-functioning, fully customizable web server application to trigger and schedule scripts. ... -
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Interpret-Text
State-of-the-art explainers for text-based machine learning models
A library that incorporates state-of-the-art explainers for text-based machine learning models and visualizes the result with a built-in dashboard. Interpret-Text builds on Interpret, an open source python package for training interpretable models and helping to explain blackbox machine learning systems. We have added extensions to support text models. Interpret-Text incorporates community-developed interpretability techniques for NLP models and a visualization dashboard to view the results. ... -
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GDAL wheels for linux
GDAL wheels for python and C/C++ projects (Linux only)
To use precompiled wheels: 1) go to releases (Files) and download tarball needed; 2) install it with command: python3 -m pip install /path/to/wheel.whl Or simply use URL in pip: python3 -m pip install https://sourceforge.net/projects/gdal-wheels-for-linux/files/GDAL-3.1.4-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl/download URL may be found under "View details" button (i) To use GDAL in C/C++ project you need to link gdal lib AND all libs located at dir GDAL.libs (usually this folder resides inside python site-packages) To compile your own wheels see information given at forefather project: https://github.com/youngpm/gdalmanylinux Usually this is done via command `make wheels` GDAL wheels for Windows are provided by Christoph Gohlke at https://www.lfd.uci.edu/~gohlke/pythonlibs/#gdal Built with PROJ (proj.db is included), GEOS, EXPAT. See Dockerfile.wheels for additional components. -
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igel
Machine learning tool that allows you to train and test models
...Whether to build some proof of concept, create a fast draft model to prove a point or use auto ML. I find myself often stuck writing boilerplate code and thinking too much about where to start. Therefore, I decided to create this tool. igel is built on top of other ML frameworks. It provides a simple way to use machine learning without writing a single line of code. Igel is highly customizable, but only if you want to. Igel does not force you to customize anything. Besides default values, igel can use auto-ml features to figure out a model that can work great with your data.
