Search Results for "cover" - Page 4
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Showing 605 open source projects for "cover"
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Managed Cybersecurity Platform Built for MSPsIn a world that lives and breathes all things digital, every business is at risk. Cybersecurity has become a major problem for small and growing businesses due to limited budgets, resources, time, and training. Hackers are leveraging these vulnerabilities, and most of the existing cybersecurity solutions on the market are too cumbersome, too complicated, and far too costly.
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Endpoint Protection Software for Businesses | HYPERSECUREThe HYPERSECURE endpoint protection platform is a comprehensive suite of products and services enhanced by European third-party solutions. It ensures our customers’ IT security, regulatory compliance, and digital sovereignty.
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Generative AI Use Cases (GenU)
Application implementation with business use cases
...Each example typically includes infrastructure templates, backend services, and application code that show how to integrate generative AI capabilities with other AWS services. These examples cover tasks such as document analysis, conversational assistants, content generation, and knowledge retrieval systems. The repository is intended to serve as both a learning resource and a starting point for developers who want to deploy generative AI solutions using AWS infrastructure. -
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Comprehensive Rust
This is the Rust course used by the Android team at Google
...Originally created for Google engineers, it has since been released publicly for the broader developer community. The course is structured into modular lessons that cover the fundamentals of Rust, including ownership, lifetimes, traits, generics, and error handling, before progressing to advanced topics like concurrency, async programming, unsafe Rust, and FFI. It is designed to be taught in classroom settings but can also be followed independently, making it useful both for structured training and self-study. ... -
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Html Menu Generator
Html menu generator
...All classes provide a human-readable, fluent interface (no array configuration). Additionally, you can opt for a more verbose and flexible syntax, or for convenience methods that cover most use cases. You can programmatically add html classes and attributes to any item in the menu, or to the menu itself. You can add id, so you can easily target some of these elements with CSS or JS. The Laravel version of the menu package adds some extras like convenience methods for generating URLs and macros. -
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TorchCode
Practice implementing softmax, attention, GPT-2 and more
...It is structured similarly to competitive programming platforms like LeetCode but focuses specifically on tensor operations and deep learning concepts. The platform provides a collection of curated problems that cover fundamental topics such as activation functions, normalization layers, attention mechanisms, and full transformer architectures. It runs in a Jupyter-based environment, allowing users to write, test, and debug their code interactively while receiving immediate feedback. An automated judging system evaluates correctness, gradient flow, and numerical stability, helping users understand both functional and theoretical aspects of their implementations. -
Solve Your Real-world Business Challenges From A Single Timesheet With Powerful Built In IntegrationTimeControl is a multi-purpose timesheet system designed to serve both Finance and Project Management. TimeControl has been designed to serve many purposes simultaneously. TimeControl tracks time on a task-by-task, project-by-project basis. Yet, despite its project-based controls, it remains a financial timesheet with all the controls necessary to fulfill the stringent needs of payroll, human resources, billing and finance. TimeControl is available both for subscription in the cloud or for purchase for an on premise installation and includes both a browser interface and the free TimeControl Mobile App for iOS and Android devices.
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DevOps Exercises
Linux, Jenkins, AWS, SRE, Prometheus, Docker, Python, Ansible, Git
DevOps Exercises is a massive, community-maintained collection of questions, tasks, and mini-challenges that cover the breadth of modern DevOps and platform engineering. It spans Linux, networking, Docker, Kubernetes, CI/CD, monitoring, cloud providers, security, and even soft skills and troubleshooting. The idea is to give candidates and teams a realistic practice ground for interviews, certifications, and day-to-day operational work. Because it’s structured as Q&A and exercises, you can go through it progressively or dip into specific domains where you need strengthening. ... -
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Solon
Java enterprise application development framework
...It advertises large concurrency gains, lower memory use, much faster startup, and dramatically smaller packages while remaining compatible from Java 8 through Java 24. The framework focuses on restrained APIs and an open ecosystem, with modules that cover web, data, cloud, and microservice patterns. Its messaging emphasizes “replaceable Spring” ergonomics—keeping developer familiarity while reducing overhead and improving deployment characteristics. Releases and companion repositories present an active community and production-oriented guidance. The broader Solon org also maintains AI/agent extensions (e.g., MCP components) that complement application development. -
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DINOv2
PyTorch code and models for the DINOv2 self-supervised learning
...The repository includes code for training, evaluating, and feature extraction, with utilities to run k-NN or linear evaluation baselines to assess representation quality. Pretrained checkpoints cover multiple model sizes so practitioners can trade accuracy for speed and memory depending on their deployment constraints. -
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MusicBrainz Server
Server for the MusicBrainz project (website, API, database tools)
...It handles artist, album, track, and recording entities and allows users to submit edits, vote, merge duplicates, and browse relationships like releases or linked ISRCs. The server supports full-text search, advanced filtering, web APIs, data dumps, and integration with other services like Cover Art Archive and Discogs. Its architecture ensures referential integrity and versioned change tracking so edits can be audited or reverted, and moderation workflows manage conflicting contributions. On the backend it uses a relational store optimized for complex joins and fast search indices. Internationalization, release group types, tagging, and flexible entity relationships reflect the complexity of music cataloging. ... -
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aisuite
Simple, unified interface to multiple Generative AI providers
...It is a thin wrapper around Python client libraries and allows creators to seamlessly swap out and test responses from different LLM providers without changing their code. Today, the library is primarily focused on chat completions. We will expand it to cover more use cases in the near future. Currently supported providers are - OpenAI, Anthropic, Azure, Google, AWS, Groq, Mistral, HuggingFace and Ollama. To maximize stability, aisuite uses either the HTTP endpoint or the SDK for making calls to the provider. -
viewneo - Smart software for digital advertising boardsviewneo is a user-friendly, cloud-based solution that allows companies of all sizes to set up digital signage
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SparkleShare
Share and collaborate by syncing with any Git repository
...You can add remotely hosted folders (or "projects") to this folder. These projects will be automatically kept in sync with both the host and all of your peers when someone adds, removes or edits a file. SparkleShare was made to cover certain use cases, but doesn't handle every scenario well. SparkleShare uses the version control system Git under the hood, so setting up a host yourself is relatively easy. Using your own host gives you more privacy and control, as well as lots of cheap storage space and higher transfer speeds. The idea of SparkleShare sprouted at the GNOME Usability Hackfest in London, where a couple of designers came to the conclusion that they didn't have a good (Open Source) collaboration tool to share their work. -
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factory_bot
A library for setting up Ruby objects as test data
...If you're creating ActiveRecord objects, that means that you should only provide attributes that are required through validations and that do not have defaults. Other factories can be created through inheritance to cover common scenarios for each class. -
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Jspreadsheet CE
Javascript plugin to create web-based tables & spreadsheets
...It is very easy to integrate any third party JavaScript plugins to create your own custom columns, custom editors, and customize any feature into your application. Jspreadsheet CE has plenty of different input options through its native column types to cover the most common web-based application requirements. It is a complete solution for web data management. Create amazing applications with Jspreadsheet CE JavaScript spreadsheet. -
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Useful Java links
A list of useful Java frameworks, libraries, software and hello worlds
...The project organizes hundreds of links to libraries, development frameworks, tutorials, and technical references that are useful for both beginner and advanced Java developers. These resources cover many areas of software development, including web frameworks, testing libraries, concurrency tools, build systems, microservices architectures, and development best practices. By grouping links into categorized sections, the repository allows developers to quickly discover relevant technologies and learning materials for building Java applications. ... -
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MLOps Zoomcamp
Free MLOps course from DataTalks.Club
...The course is designed to teach data scientists and engineers how to move machine learning models from experimentation environments into scalable production services. The repository provides lessons, code examples, and assignments that cover the entire MLOps lifecycle, including model training, experiment tracking, deployment, monitoring, and infrastructure management. Students learn to use widely adopted tools such as MLflow, orchestration frameworks, and cloud platforms to manage machine learning pipelines. The curriculum emphasizes hands-on projects so learners gain practical experience building automated ML pipelines and maintaining deployed models. -
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golib
Golang packages used in frp and fft
...It serves as a shared foundation for IO helpers, messaging formats, and other utilities that would otherwise be copy-pasted between codebases. The repository is versioned and published as Go modules, making it easy to import stable subsets into downstream applications. Individual subpackages cover concerns like streaming IO and JSON message structures, keeping implementations small and composable. By consolidating these pieces, the ecosystem around frp/fft benefits from consistent behavior and fewer bespoke dependencies. The code is released under the Apache-2.0 license, enabling broad adoption in both open and closed source contexts. -
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Deep Learning Is Nothing
Deep learning concepts in an approachable style
...Once the fundamentals are clear, the material extends to CNNs, RNNs, and attention mechanisms, explaining why each architecture suits particular tasks. Practical sections cover data pipelines, regularization, and evaluation, emphasizing reproducibility and debugging techniques. The goal is to replace buzzwords with intuition so learners can reason about architectures and training dynamics with confidence. -
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Apache Seata
High-performance, open source distributed transaction solution
...The AT mode is notable for minimizing code changes: Seata captures before/after images of SQL updates and can roll back on failure to maintain atomicity across services. Integrations cover common RPC frameworks and registries, enabling drop-in usage within Spring Cloud/Dubbo-style ecosystems. -
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Computer Science Flash Cards
Mini website for testing both general CS knowledge and enforce coding
This repository collects concise flash cards that cover the core ideas of a traditional computer science curriculum with a focus on interview readiness. The cards distill topics like time and space complexity, classic data structures, algorithmic paradigms, operating systems, networking, and databases into short, testable prompts. They are designed for spaced-repetition style study so you can cycle frequently through fundamentals until recall feels automatic. -
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Machine Learning Foundations
Machine Learning Foundations: Linear Algebra, Calculus, Statistics
...The project focuses on explaining the fundamental mathematical and computational concepts that underpin modern machine learning and artificial intelligence systems. The materials cover essential topics such as linear algebra, calculus, statistics, and probability, which form the theoretical basis of many machine learning algorithms. The repository includes Jupyter notebooks with explanations and examples that demonstrate how these mathematical principles relate to real machine learning applications. Each section introduces theoretical concepts and then illustrates them through practical coding examples to reinforce understanding. ... -
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Data-Science-Interview-Questions-Answers
Curated list of data science interview questions and answers
...The repository focuses on core data science fundamentals rather than acting as a software framework, which makes it especially useful as a study and revision resource. Its content is organized into subject-specific documents that cover machine learning, deep learning, statistics, probability, Python, SQL and databases, and resume-based interview questions. That structure makes it practical for users who want to study by topic, strengthen weak areas, or simulate the range of questions they may encounter in interviews. -
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learning
A log of things I'm learning
...Rather than being a traditional software library, the repository acts as a structured knowledge base documenting the author’s ongoing learning journey across topics such as programming, system design, machine learning, and generative AI. The content is organized into categories that cover both core engineering skills and adjacent technologies, enabling readers to follow a practical roadmap for developing strong technical foundations. The repository emphasizes clear explanations, curated resources, and concise notes designed to help developers learn complex topics efficiently. Because it is updated regularly, it reflects evolving trends in software engineering and emerging technologies such as modern AI systems. -
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Data Science Interviews
Data science interview questions and answers
...The repository organizes questions into different categories including theoretical machine learning concepts, technical programming questions, and probability or statistics problems. Many of the questions cover fundamental machine learning topics such as linear models, decision trees, neural networks, and evaluation metrics. In addition to theoretical questions, the repository also includes practical interview topics related to coding challenges, SQL queries, and algorithmic thinking. -
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AI Engineering Transition Path
Research papers and blogs to transition to AI Engineering
AI Engineering Resources is an open educational repository that compiles research papers, tutorials, and learning materials for software engineers transitioning into artificial intelligence engineering roles. The project organizes resources that cover fundamental topics required to understand modern AI systems, including transformers, vector embeddings, tokenization, infrastructure design, and mixture-of-experts architectures. Instead of presenting isolated tutorials, the repository provides a structured pathway that guides engineers through the technical knowledge needed to build and deploy large language model systems. ... -
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vimrc
The ultimate Vim configuration (vimrc)
amix/vimrc is a popular, batteries-included Vim configuration that aims to make Vim productive from the very first launch. It ships with a curated set of sensible defaults, mappings, and plugins that cover editing, navigation, search, Git, and language tooling. The project offers two tracks—a full configuration and a lightweight version—so you can choose between a maximal setup or a leaner base. Installation is intentionally simple, relying on a single command that clones and bootstraps everything into place. The repo is opinionated about ergonomics: consistent leader mappings, improved motions, and polished statusline settings reduce friction for everyday work. ... -
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Uncertainty Baselines
High-quality implementations of standard and SOTA methods
...Rather than offering toy scripts, it provides end-to-end recipes—data input, model architectures, training loops, evaluation metrics, and logging—so results are comparable across runs and research groups. The library spans canonical modalities and tasks, from image classification and NLP to tabular problems, with baselines that cover both deterministic and probabilistic approaches. Techniques include deep ensembles, Monte Carlo dropout, temperature scaling, stochastic variational inference, heteroscedastic heads, and out-of-distribution detection workflows. Each baseline emphasizes reproducibility: fixed seeds, standard splits, and strong metrics such as calibration error, AUROC for OOD, and accuracy under shift.
