Search Results for "setup" - Page 8
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Showing 298 open source projects for "setup"
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Auth0 for AI Agents now in GAConnect your AI agents to apps and data more securely, give users control over the actions AI agents can perform and the data they can access, and enable human confirmation for critical agent actions.
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Field Service+ for MS Dynamics 365 & SalesforceResco’s mobile solution streamlines your field service operations with offline work, fast data sync, and powerful tools for frontline workers, all natively integrated into Dynamics 365 and Salesforce.
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SimSiam
PyTorch implementation of SimSiam
...The repository provides scripts for both unsupervised pre-training and linear evaluation, using a ResNet-50 backbone by default. It is compatible with multi-GPU distributed training and can be fine-tuned or transferred to downstream tasks like object detection following the same setup as MoCo. -
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Ansible Role: prometheus
Deploy Prometheus monitoring system
Ansible-Prometheus is an Ansible role for automating the deployment and configuration of Prometheus monitoring systems. -
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CommanderPi
Easy RaspberryPi4 GUI system managment
Easy Raspberry Pi 4 GUI system manager. -
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VITS
Conditional Variational Autoencoder with Adversarial Learning
...The repository provides training and inference pipelines for common datasets such as LJ Speech (single-speaker) and VCTK (multi-speaker), including filelists, configs, and preprocessing scripts. It also includes monotonic alignment search code and g2p preprocessing, which are crucial components for aligning text and speech in an end-to-end setup. -
Inventors: Validate Your Idea, Protect It and Gain Market AdvantagessenseIP is an AI innovation platform for inventors, automating any aspect of IP from the moment you have an idea. You can have it researched for uniqueness and protected; quickly and effortlessly, without expensive attorneys. Built for business success while securing your competitive edge.
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EH Forwarder Bot
An extensible message tunneling chat bot framework
...When you have successfully installed the modules of your choices, you can the use the configuration wizard which guides you to enable channels and middlewares, and continue to setup those modules. -
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...Proceed at own risk. Working knowledge of Linux and Windows computers required. This is not a tutorial on how to use your computers. Still here? Awesome! This setup works with a connected PC. You can watch movies and play games with the backglow running. Adds extra ambience to your expeirence. Especially as you transition from bright outdoor scenes to darker indoors ones.
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ClamWin
Antivirus software with virus scanning and virus definition updates
...Free Antivirus software for Windows, using the well-respected ClamAV scanning engine. Includes virus scanner, scheduler, virus database updates, context menu integration to MS Windows Explorer and Add-in to MS Outlook. Also features easy setup program. -
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Big List of Naughty Strings
List of strings which have a high probability of causing issues
...By throwing these strings at forms, APIs, databases, and UIs, teams can discover encoding bugs, sanitizer gaps, rendering issues, and security oversights early. The list is language-agnostic and repository-friendly, meaning you can consume it from CI pipelines or local scripts with minimal setup. Because it’s crowdsourced, it reflects real issues practitioners have faced in production, not just theoretical cases. Using the list regularly helps harden applications against the fragile edges of text processing and user input. -
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FastAPI + React
Cookiecutter Template for FastAPI
FastAPI-React is a cookiecutter template that combines FastAPI and React to create full-stack applications. It integrates PostgreSQL, SQLAlchemy, and Docker to provide a comprehensive development environment. -
Automated RMM Tools | RMM SoftwareOut-of-the-box scripts. Around-the-clock monitoring. Unmatched automation capabilities. Start doing more with less and exceed service delivery expectations.
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BudgetML
Deploy a ML inference service on a budget in 10 lines of code
...BudgetML is our answer to this challenge. It is supposed to be fast, easy, and developer-friendly. It is by no means meant to be used in a full-fledged production-ready setup. It is simply a means to get a server up and running as fast as possible with the lowest costs possible. -
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Flask-MongoEngine
MongoEngine flask extension with WTF model forms support
...Integration with WTFForms and FlaskDebugToolbar are optional and should be selected as extra option, if required. This is done by users request, to limit amount of external dependencies in different production setup environments. All methods end extras described below are compatible between each other and can be used together. We still maintain special case for Flask = 1.1.4 support (the latest version in 1.x.x branch). To install flask-mongoengine with required dependencies use legacy extra option. Flask-mongoengine can be installed with Flask-WTF and WTFForms support. ... -
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SageMaker MXNet Training Toolkit
Toolkit for running MXNet training scripts on SageMaker
SageMaker MXNet Training Toolkit is an open-source library for using MXNet to train models on Amazon SageMaker. For inference, see SageMaker MXNet Inference Toolkit. For the Dockerfiles used for building SageMaker MXNet Containers, see AWS Deep Learning Containers. For information on running MXNet jobs on Amazon SageMaker, please refer to the SageMaker Python SDK documentation. With the SDK, you can train and deploy models using popular deep learning frameworks Apache MXNet and TensorFlow.... -
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AlphaPy
Python AutoML for Trading Systems and Sports Betting
...Built on popular libraries like scikit-learn and pandas, it enables data scientists and speculators to craft predictive models, ensemble strategies, and automated forecasting systems with minimal setup. Run machine learning models using scikit-learn, Keras, xgboost, LightGBM, and CatBoost. Generate blended or stacked ensembles. Create models for analyzing the markets with MarketFlow. Develop trading systems and analyze portfolios using MarketFlow and Quantopian's pyfolio. -
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motionEyeOS
A video surveillance OS for single-board computers
motionEyeOS is a Linux distribution that turns a single-board computer into a video surveillance system. The OS is based on BuildRoot and uses motion as a backend and motionEye for the frontend. Compatible with most USB cameras as well as with the Raspberry PI camera module. Motion detection with email notifications and working schedule. JPEG files for still images, AVI files for videos. Connects to your local network using ethernet or wifi. File storage on SD card, USB drive or network SMB... -
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Albedo
A recommender system for discovering GitHub repos
...The project focuses on implicit feedback—stars, watches, and other engagement metrics—so it can build useful recommendations without explicit ratings. A reproducible setup and Makefile-driven workflow streamline tasks like spinning up services, loading datasets, training models, and generating candidate lists. Because it’s built around Spark’s scalable primitives, Albedo can experiment on substantial snapshots of GitHub metadata rather than toy corpora. The repo is also educational: it demonstrates a practical end-to-end pipeline from ingestion and feature preparation to training and ranking. -
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Streisand
Streisand sets up a new server running your choice
...This includes OpenVPN, WireGuard, Shadowsocks, OpenConnect, and Tor bridges, often with optional add-ons like obfuscation or stunnel to resist throttling and detection. The result is a private website that hosts client software downloads and setup instructions for easy access. Streisand supports major cloud providers like AWS, Azure, Google Cloud, Linode, DigitalOcean, and Rackspace, while also offering installation options for advanced users with their own servers. -
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API Correios
API correios.com.br in Python
pycorreios is a Python library aimed at interacting with Brazil’s postal service (Correios) APIs, making it easier for developers to track shipments, calculate postage, query service availability, and integrate with Brazilian e-commerce flows. The library abstracts the raw SOAP or REST endpoints exposed by Correios, providing Pythonic methods to perform common tasks like tracking a package by its code or computing shipping cost/lead time between postal codes. It handles serialization and... -
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Affine Transformation of Virtual Object
Transformation virtual 3D object using a finger gesture-based system
Affine transformation virtual 3D object using a finger gesture-based interactive system in the virtual environment. A convolutional neural network (CNN) based thumb and index fingertip detection system are presented here for seamless interaction with a virtual 3D object in the virtual environment. First, a two-stage CNN is employed to detect the hand and fingertips, and using the information of the fingertip position, the scale, rotation, translation, and in general, the affine... -
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BytePS
A high performance and generic framework for distributed DNN training
...We use Tesla V100 32GB GPUs and set batch size equal to 64 per GPU. Each machine has 8 V100 GPUs (32GB memory) with NVLink-enabled. Machines are inter-connected with 100 Gbps RDMA network. This is the same hardware setup you can get on AWS. -
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TensorFlow Course
Simple and ready-to-use tutorials for TensorFlow
This repository houses a highly popular (~16k stars) set of TensorFlow tutorials and example code aimed at beginners and intermediate users. It includes Jupyter notebooks and scripts that cover neural network fundamentals, model training, deployment, and more, with support for Google Colab. -
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PyTorch Natural Language Processing
Basic Utilities for PyTorch Natural Language Processing (NLP)
...With your batch in hand, you can use PyTorch to develop and train your model using gradient descent. For example, check out this example code for training on the Stanford Natural Language Inference (SNLI) Corpus. Now you've setup your pipeline, you may want to ensure that some functions run deterministically. Wrap any code that's random, with fork_rng and you'll be good to go. Now that you've computed your vocabulary, you may want to make use of pre-trained word vectors to set your embeddings. -
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yapyutils
Utilities for platform indepentent low-level system APIs.
... * *yapyutils.files* Search and location of files, e.g. modules and configuration files. * *yapyutils.help* Simple help for command line interfaces. * *yapyutils.config* Configuration file support, in particular for the initial setup of software packages. -
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yapydata
Lower-Layer unified data - JSON, XML, YAML + INI, CFG, properties
...Therefore it encapsulates the libraries by offering a common API with the canonical internal data as JSON compatible Python in-memory structure. The application is foreseen in particular for the lower layer of the software stack including setup-tools. Thus it uses standard libraries only whenever possible. The initial supported DDLs are: * JSON, XML, YAML and the formats * INI, CFG, .properties The yapydata in particular supports the advanced access to data entries by mapping the dotted-OID notation onto mixed in-memory data types, optional including non-conformant tyeps such as tuple and set. -
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Defox text to speech and downloader
Written or imported text offline read or online download.
This software design to convert text to speech and download the converted speech. Description : • Installation setup with two languages (English, French) • Two areas called text reading and speech downloading • Many languages supported to download center Note 1: I'm a student yet and I'm not in the software designing industry. Therefore maybe I haven't software making skills. I'm worried about that. ! Note 2 : When you double click on the software maybe it will get some seconds to open. ... -
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UnsupervisedMT
Phrase-Based & Neural Unsupervised Machine Translation
...The project also provides scripts to fetch and preprocess monolingual data, learn BPE codes, and train cross-lingual embeddings that bootstrap unsupervised alignment between languages. Beyond the core EMNLP 2018 setup, the codebase exposes additional, optional capabilities such as multi-language training, language model pretraining with shared parameters, and adversarial training.
