Search Results for "tutorial" - Page 5
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Showing 883 open source projects for "tutorial"
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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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Next-Gen Encryption for Post-Quantum Security | CLEAR by Quantum KnightCLEAR by Quantum Knight is a FIPS-140-3 validated encryption SDK engineered for enterprises requiring top-tier security. Offering robust post-quantum cryptography, CLEAR secures files, streaming media, databases, and networks with ease across over 30 modern platforms. Its compact design, smaller than a single smartphone image, ensures maximum efficiency and low energy consumption.
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GraphQL Java
GraphQL Java implementation
GraphQL Java implementation. It requires a little Spring and Java knowledge. GraphQL is a query language to retrieve data from a server. It is an alternative to REST, SOAP or gRPC. One very important property of GraphQL is that it is statically typed: the server knows exactly the shape of every object you can query and any client can actually "introspect" the server and ask for the "schema". The schema describes what queries are possible and what fields you can get back. (Note: when we refer... -
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Responsive Framework
Easily make Flutter apps responsive. Automatically adapt UI
Responsive Framework adapts your UI to different screen sizes automatically. Create your UI once and have it display pixel-perfect on mobile, tablet, and desktop! Supporting multiple display sizes often means recreating the same layout multiple times. Under the traditional Bootstrap approach, building responsive UI is time-consuming, frustrating and repetitive. Furthermore, getting everything pixel-perfect is nearly impossible and simple edits take hours. AutoScale shrinks and expands your... -
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Critical
Extract & Inline Critical-path CSS in HTML pages
Critical extracts & inlines critical-path (above-the-fold) CSS from HTML. Generate and inline critical-path CSS. Generate critical-path CSS. Generate and minify critical-path CSS. Generate, minify and inline critical-path CSS. Generate and return output via callback. Generate and return output via promise. When your site is adaptive and you want to deliver critical CSS for multiple screen resolutions this is a useful option. note, (your final output will be minified as to eliminate duplicate... -
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shot-scraper
A command-line utility for taking automated screenshots of websites
...The project is deeply integrated with automation workflows: examples show it running in scheduled jobs, GitHub Actions, and bots that publish screenshots to social media or use them in docs. It ships with detailed documentation, a tutorial, and a template repository that lets you spin up an automated screenshot pipeline. -
Collect! is a highly configurable debt collection softwareThe flexible & scalable debt collection software built to automate your workflow. From startup to enterprise, we have the solution for you.
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Python Code Tutorials
The Python Code Tutorials
...The repository covers a wide range of programming topics including cybersecurity, networking, web scraping, machine learning, GUI development, and automation scripts. Each tutorial typically includes complete Python code examples and explanations that demonstrate how to build real tools and applications step by step. Many tutorials focus on practical implementations such as building network scanners, web scraping tools, object detection systems, and automation utilities using Python libraries. The repository is organized into thematic directories that group tutorials by topic, allowing learners to navigate easily between areas such as ethical hacking, multimedia processing, or machine learning. -
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Kaggle Solutions
Collection of Kaggle Solutions and Ideas
Kaggle Solutions is an open-source repository that compiles winning solutions, insights, and educational resources from hundreds of Kaggle data science competitions. The repository acts as a knowledge base for competitive machine learning by collecting solution write-ups, discussion threads, code notebooks, and tutorial resources shared by top Kaggle participants. Each competition entry typically includes information about the dataset, evaluation metrics, modeling strategies, and techniques used by high-ranking competitors. The repository also highlights important machine learning concepts such as feature engineering, cross-validation strategies, ensemble modeling, and post-processing methods commonly used in winning solutions. ... -
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Made With ML
Learn how to develop, deploy and iterate on production-grade ML
Made-With-ML is an open-source educational repository and course designed to teach developers how to build production-grade machine learning systems using modern MLOps practices. The project focuses on bridging the gap between experimental machine learning notebooks and real-world software systems that can be deployed, monitored, and maintained at scale. It provides structured lessons and practical code examples that demonstrate how to design machine learning workflows, manage datasets,... -
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AI Engineering Hub
In-depth tutorials on LLMs, RAGs and real-world AI agent applications
The AI Engineering Hub repository is a large open-source collection of hands-on projects, tutorials, and real-world AI engineering resources designed to help developers learn and build with modern AI technologies, especially large language models (LLMs), retrieval-augmented generation (RAG), and agent-based systems. It includes more than 90 production-ready projects across skill levels, organized into beginner, intermediate, and advanced categories to guide users progressively from simple... -
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100 proyectos de JavaScript
100 JavaScript projects with code and videos for free
100 proyectos de JavaScript is a large collection of 100 JavaScript projects, each with source code and an accompanying video tutorial, offered entirely for free. The repository is tied to the website javascript100.dev, which presents the projects as a structured learning path so learners can progressively build their skills through practice.Each project lives in its own numbered folder (for example, 01-tinder-swipe), and the README explains how to run them via the VS Code Live Preview extension, making it easy for beginners to get them running without complex tooling. ... -
Premier Construction SoftwareRated #1 Construction Accounting Software by Forbes Advisor in 2022 & 2023. Our modern SAAS solution is designed to meet the needs of General Contractors, Developers/Owners, Homebuilders & Specialty Contractors.
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Mistral Finetune
Memory-efficient and performant finetuning of Mistral's models
...It supports function-calling style datasets (via "messages" keys) as well as plain text formats, with guidelines on formatting, tokenization, and vocabulary extension (e.g. extending vocab to 32768 for some models) before finetuning. The project also provides tutorial notebooks (e.g. mistral_finetune_7b.ipynb) to walk through the steps. -
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mlpack
mlpack: a scalable C++ machine learning library
...Aims to provide fast, extensible implementations of cutting-edge machine learning algorithms. mlpack uses CMake as a build system and allows several flexible build configuration options. You can consult any of the CMake tutorials for further documentation, but this tutorial should be enough to get mlpack built and installed. -
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Easy-Vibe
Tutorial on Product Prototype, AI Capability Integration
Easy-Vibe is an open-source educational project designed to teach developers, product managers, and beginners how to build AI-powered applications using the emerging concept of “vibe coding,” a development approach that relies heavily on AI-assisted programming tools. The project provides a structured curriculum that guides learners from having no programming experience to building fully functional AI-integrated applications. Instead of focusing only on theoretical concepts, Easy-Vibe... -
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NVIDIA Generative AI Examples
Generative AI reference workflows
NVIDIA GenerativeAIExamples is an open-source repository that provides practical reference implementations and example workflows for building generative AI applications using NVIDIA’s software ecosystem. The project is designed to help developers accelerate the development of AI applications by providing ready-to-run pipelines, notebooks, and tools that demonstrate how to integrate large language models into real-world systems. The repository includes examples covering topics such as... -
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PyTorch Geometric Temporal
Spatiotemporal Signal Processing with Neural Machine Learning Models
...The package interfaces well with Pytorch Lightning which allows training on CPUs, single and multiple GPUs out-of-the-box. PyTorch Geometric Temporal makes implementing Dynamic and Temporal Graph Neural Networks quite easy - see the accompanying tutorial. Head over to our documentation to find out more about installation, creation of datasets and a full list of implemented methods and available datasets. -
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EF Core
Object-database mapper for .NET
...EF Core works with many databases, including SQL Database (on-premises and Azure), SQLite, MySQL, PostgreSQL, and Azure Cosmos DB. To install EF Core, you install the package for the EF Core database provider(s) you want to target. This tutorial uses SQLite because it runs on all platforms that .NET Core supports. This application intentionally keeps things simple for clarity. Connection strings should not be stored in the code for production applications. You may also want to split each C# class into its own file. Query and manage relational data in a .NET Core app with an Object-Relational Mapper (O/RM). -
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leafmap
A Python package for interactive mapping and geospatial analysis
A Python package for geospatial analysis and interactive mapping in a Jupyter environment. Leafmap is a Python package for interactive mapping and geospatial analysis with minimal coding in a Jupyter environment. It is a spin-off project of the geemap Python package, which was designed specifically to work with Google Earth Engine (GEE). However, not everyone in the geospatial community has access to the GEE cloud computing platform. Leafmap is designed to fill this gap for non-GEE users. It... -
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Evennia
Python MUD/MUX/MUSH/MU* development system
Evennia is a mature, open-source framework written in Python — specifically designed to build text-based, online multiplayer games such as MUDs, MUCKs, MUSHes, MUXes, and other “MU-style” virtual worlds. Rather than prescribing a rigid game structure, Evennia gives you a bare-bones but powerful foundation: default systems handle networking, database/storage, server management, user accounts, characters, rooms, items, chat channels, and basic commands — but you define the gameplay rules,... -
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Networked-Aframe
Web framework for building multi-user virtual reality experiences
Multi-user VR on the Web. A framework for writing multi-user VR apps in HTML and JS. Built on top of A-Frame. Follow the NAF Getting Started tutorial to build your own example from scratch, including setting up a local server. Networked-Aframe works by syncing entities and their components to connected users. To connect to a room you need to add the networked-scene component to the a-scene element. For an entity to be synced, add the networked component to it. By default the position and rotation components are synced, but if you want to sync other components or child components you need to define a schema. ... -
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GoNB
GoNB, a Go Notebook Kernel for Jupyter
...It already includes many goodies: cache between cell of results, contextual help and auto-complete (with gopls), compilation error context (by mousing over), bash command execution, images, html, etc. See the tutorial. It's been heavily used by the author (in developing GoMLX, a machine learning framework for Go), but should still be seen as experimental — if we hear success stories from others, we can change this. -
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A Matlab toolkit for all aspects of EEG/ERP analysis, especially PCA. If you run into a problem, please send me a note and I'll fix it. The tutorial pdf is in the documentation folder and the tutorial data can be downloaded from a link provided by the pdf. The tutorial file has full install instructions. For all platforms supported by Matlab.
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Katalog
Catalog your devices to search, analyze, and backup your files.
Catalog your devices to search, analyze, and backup your files: - Create catalogs from different sources or devices - Search and explore files even when the devices are disconnected - Organize and backup your collection of files, and get statistics User documentation: - Get started/Tutorial: https://stephanecouturier.github.io/Katalog/docs/tutorial - Download (Linux Flathub): https://flathub.org/en/apps/io.github.stephanecouturier.Katalog - Documentation: https://stephanecouturier.github.io/Katalog/docs/Overview - Development: https://stephanecouturier.github.io/Katalog/docs/Development-Overview - Facebook: https://www.facebook.com/Katalog-107117844916308 -
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GLFW
A multi-platform library for OpenGL, OpenGL ES, Vulkan, etc.
...Support for multiple windows, multiple monitors, high-DPI and gamma ramps. Support for keyboard, mouse, gamepad, time and window event input, via polling or callbacks. Comes with a tutorial, guides and reference documentation, examples and test programs. Open Source with an OSI-certified license allowing commercial use. Access to native objects and compile-time options for platform specific features. Community-maintained bindings for many different languages. -
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Here is my Tool for Auto compare Stack View in CE. https://youtu.be/PTW8hmar_CI Here is My cheat engine Tutorial: https://cheatengineguide.blogspot.com/2025/02/ce-guide.html
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CometAnalyser
CometAnalyser, for quantitative comet assay analysis.
...CometAnalyser is an open-source deep-learning tool designed for the analysis of both fluorescent and silver-stained wide-field microscopy images. Once the comets are segmented and classified, several intensity/morphological features are automatically exported as a spreadsheet file. Video Tutorial: CometAnalyser is written in MATLAB. It works with Windows, Macintosh, and UNIX-based systems. Please, download the sample datasets and test it watching the video tutorial to understand how it works: https://www.youtube.com/watch?v=vh2VFnMw50A Contacts: filippo.piccinini85@gmail.com beleonattila@gmail.com -
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scikit-learn-videos
Jupyter notebooks from the scikit-learn video series
scikit-learn-videos repository accompanies a video tutorial series designed to teach machine learning using Python’s scikit-learn library. It provides the Jupyter notebooks used in each lesson so learners can reproduce the demonstrations and experiment with the code themselves. The series introduces fundamental machine learning concepts such as classification, regression, model evaluation, feature engineering, and cross-validation using clear examples and real datasets.
