Search Results for "problem a" - Page 5
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Showing 1768 open source projects for "problem a"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Veeam Data Platform v13.1Try Veeam Data Platform today. Experience the unified platform that's secure by design, portable by default, and proven to recover clean, fast, and anywhere.
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CTFcrackTools
China's first CTFTools framework
The first CTF tool framework in China. China's first CTFTools framework designed to help CTFer quickly overcome the CTF problem. Use kotlin and java mixed development. This is probably the first tool framework applied to CTF in China. Built-in current mainstream password, includes but is not limited to Virginia password, Caesar password, fence password. Users can write plugs independently, but only support Python to write plugs. The writing method is also extremely simple. -
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JavaScript Algo and Data Structures
Algorithms and data structures implemented in JavaScript
...The repository covers topics such as sorting, searching, graph algorithms, cryptography, and data structures like linked lists, stacks, and queues. It is designed to help developers understand algorithm fundamentals and practice problem-solving with JavaScript. Multilingual README files make the resource accessible to a global audience. With strong community engagement, it is one of the most popular algorithm repositories on GitHub. -
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Project Based Learning
Curated list of project-based tutorials
...The collection spans various domains including web development, game programming, systems programming, and machine learning. By following the projects, learners can strengthen problem-solving skills, gain experience with different technologies, and build portfolios. The repository grows with community contributions, making it a dynamic resource for developers at all levels. -
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Micronaut Data
Ahead of Time Data Repositories
...Both GORM and Spring Data maintain a runtime meta-model that uses reflection to model relationships between entities. This model consumes significant memory and memory requirements grow as your application size grows. The problem is worse when combined with Hibernate which maintains its own meta-model as you end up with duplicate meta-models. Micronaut Data instead moves this model into the compiler. Both GORM and Spring Data use regular expressions and pattern matching in combination with runtime generated proxies to translate a method definition on a Java interface into a query at runtime. ... -
99.99% Uptime for MySQL and PostgreSQL DatabasesCloud SQL Enterprise Plus delivers near-zero downtime with 35 days of point-in-time recovery. Supports MySQL, PostgreSQL, and SQL Server.
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virtualenv
Virtual Python environment builder
...It creates an environment that has its own installation directories, that doesn’t share libraries with other virtualenv environments (and optionally doesn’t access the globally installed libraries either). The basic problem being addressed is one of dependencies and versions, and indirectly permissions. Imagine you have an application that needs version 1 of LibFoo, but another application requires version 2. How can you use both these libraries? If you install everything into your host python (e.g. python3.8) it’s easy to end up in a situation where two packages have conflicting requirements. -
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Glamorous Toolkit
Glamorous Toolkit is the Moldable Development environment
...And this is what Glamorous Toolkit makes practical. Glamorous Toolkit is the Moldable Development environment. It empowers you to make systems explainable through experiences tailored for each problem. -
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Impetus
A key remapping daemon for linux
...In order to achieve satisfactory results a medley of tools need to be employed (e.g xcape, xmodmap) with the end result often being tethered to a specified environment (X11). keyd attempts to solve this problem by providing a flexible system-wide daemon that remaps keys using kernel-level input primitives (evdev, input). -
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Genie
Distributed Big Data Orchestration Service
Genie is a completely open source distributed job orchestration engine developed by Netflix. Genie provides REST-ful APIs to run a variety of big data jobs like Hadoop, Pig, Hive, Spark, Presto, Sqoop and more. It also provides APIs for managing the metadata of many distributed processing clusters and the commands and applications which run on them. -
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METATRON
AI-powered penetration testing assistant using local LLM on linux
METATRON is a multi-agent AI orchestration framework designed to coordinate complex workflows across multiple intelligent agents. It provides a structured system for task delegation, communication, and collaboration between agents. The framework emphasizes scalability, allowing multiple agents to work together on large or complex problems. It includes mechanisms for managing context, memory, and execution flow across tasks. METATRON is particularly useful for building advanced AI systems... -
Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
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Laravel Activity Log
Log activity inside your Laravel app
...Open source software is used in all projects we deliver. Laravel, Nginx, Ubuntu are just a few of the free pieces of software we use every single day. For this, we are very grateful. When we feel we have solved a problem in a way that can help other developers, we release our code as open source software on GitHub. -
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StarVector
StarVector is a foundation model for SVG generation
StarVector is a multimodal foundation model designed for generating Scalable Vector Graphics (SVG) from images or textual descriptions. The system treats vector graphics creation as a code generation problem, producing SVG code that can render detailed vector images. Its architecture combines computer vision techniques with language modeling capabilities so it can understand visual inputs and textual prompts simultaneously. The model converts raster images or text instructions into structured vector representations, enabling high-quality vectorization and design generation. ... -
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kb
A minimalist command line knowledge base manager
kb is a minimalist command-line knowledge base manager that gives users a fast, organized way to collect, store, search, and retrieve notes, documents, cheatsheets, procedures, and other artifacts directly from the terminal. It was created to solve the common problem of having scattered text files or reference materials on disk that are hard to search or categorize, and it surfaces a simple CLI interface with intuitive commands for adding, viewing, editing, and deleting knowledge items. Each entry in kb can be tagged, categorized, given metadata like author or status, and inspected with full-text search or regex-based grepping, helping users quickly find content even across large knowledge collections. ... -
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node-red-contrib-custom-chatgpt
Node-RED ChatGPT
...Create a new secret key" then copy and paste the "API key" into the node API_KEY property value. msg.payload should be a well-written prompt that provides enough information for the model to know what you want and how it should respond. Its success generally depends on the complexity of the task and quality of your prompt. A good rule of thumb is to think about how you would write a word problem for a middle schooler to solve. msg.payload should be a well-written prompt that provides enough information for the model to know what you want and how it should respond. -
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wemake-python-styleguide
The strictest and most opinionated python linter ever!
...Fewer code revisions - strict linting ensures that you don't have to re-write the codebase again and again. Reduce code redundancy - Sometimes we write complex code as we are thinking in a certain way about a problem. The linter offers suggestions that can help simplify the code and eliminate redundant statements. The ultimate goal of this project is to make all people write exactly the same Python code. -
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Booster
Optimizer for mobile applications
...Potential performance issues could be found by using Booster, for example, calling APIs that may block the UI thread or main thread, such as I/O APIs. Thread management has always been a problem for developers, especially the threads started by third-party SDKs, starting too many threads may cause OOM, fortunately, these issues can be solved by Booster. -
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Wondel.ai Skills
Agent skills for Claude Code and other agentskills-compatible agents
...Each skill represents a structured set of instructions, workflows, and tools that enable agents to perform specific tasks with expertise. These skills can cover a wide range of domains, including development, automation, and problem-solving, allowing agents to extend their capabilities dynamically. The system emphasizes modularity, enabling skills to be reused and combined into more complex workflows. It also supports compatibility across multiple AI tools and platforms, making it a versatile resource for developers. The repository serves as both a toolkit and a marketplace of capabilities that can be installed into agents. ... -
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Agency Agents
A complete AI agency at your fingertips
...It is designed around the idea of “agency,” where each agent has a defined role, responsibility, and interaction pattern within a larger system. The framework enables developers to define workflows where agents communicate, delegate tasks, and share context, creating a distributed problem-solving environment. It supports modular design, allowing agents to be composed into reusable systems that can be adapted across different use cases. The project emphasizes clarity in agent responsibilities, which helps reduce ambiguity and improve reliability in multi-agent workflows. It also provides mechanisms for managing interactions, ensuring that communication between agents remains structured and predictable. ... -
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Open Multi-Agent
One runTeam() call from goal to result
Open Multi-Agent is a flexible framework designed to enable the creation and coordination of multiple AI agents working together to solve complex tasks through collaboration. It focuses on distributing responsibilities across specialized agents, each handling a specific part of a problem, such as planning, execution, or validation. The system emphasizes modularity, allowing developers to define agent roles, communication protocols, and workflows. It supports iterative collaboration, where agents exchange information and refine outputs collectively. The architecture is designed to be extensible, enabling integration with external tools and APIs to expand agent capabilities. ... -
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mini SWE-agent
The 100 line AI agent that solves GitHub issues
...Unlike more complex frameworks, it emphasizes simplicity and efficiency, consisting of roughly 100 lines of code while still achieving strong performance on benchmarks such as SWE-bench Verified, where it demonstrates competitive problem-solving capabilities. The agent operates by interpreting software issues, analyzing repository context, and executing actions such as editing code, running commands, and validating fixes through iterative reasoning loops. It integrates seamlessly with language models, enabling flexible deployment with different providers while maintaining a consistent workflow for automated debugging and code modification. -
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Zero to Mastery Machine Learning
All course materials for the Zero to Mastery Machine Learning
...The project provides a structured curriculum designed to teach machine learning and data science using Python through hands-on projects and interactive notebooks. The repository includes datasets, Jupyter notebooks, documentation, and example code that walk learners through the entire machine learning workflow from problem definition to model deployment. The course introduces essential tools such as NumPy, pandas, Matplotlib, and scikit-learn before moving on to deep learning with frameworks like TensorFlow and Keras. It also includes milestone projects that demonstrate how to build end-to-end machine learning systems using real datasets, including classification and regression tasks. -
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Restaurant Management System
Restaurant Management System written in Python using Tkinter
Restaurants nowadays require modern solutions to handle daily tasks, especially when it comes to order handling as bookkeeping is outdated for modern times, in which human fault might cost the facility lots of money. Restaurant Management System (will be referred as RMS from now on) offers the following to tackle the problem. Store the configuration of the given restaurant and its menu to easily handle reservations and orders. Create and store orders for the requested tables. Generate and save bills when requested. Storing the restaurant configuration: configure facility name, table/seat counts, and menu with the ability to modify them in the future. ... -
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SimpRead
An extension that allows you to instantly enter immersive reading
...Do not change the structure of the current page, just highlight the part that needs to be read, suitable for temporary reading or websites that are not adapted to the reading mode. Have pictures you don’t want to show? no problem! Any element on the page can be re-edited. The brand-new lexical analysis engine can not only recognize Wordpress, Hexo, Ghost, and Discuz, as long as it is a well-structured page, it can automatically generate a reading mode. Not only that, but also has a variety of recognition modes. -
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dlib
Toolkit for making machine learning and data analysis applications
Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. It is used in both industry and academia in a wide range of domains including robotics, embedded devices, mobile phones, and large high performance computing environments. Dlib's open source licensing allows you to use it in any application, free of charge. Good unit test coverage, the ratio of unit test lines of code to library lines of code is... -
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Napkin Math
Techniques and numbers for estimating system's performance
Napkin Math is a technical reference project for estimating software system performance from first principles. It collects practical numbers, benchmark-style measurements, and mental models that help engineers make fast back-of-the-envelope calculations. The project is useful for questions like how much memory throughput matters, how long storage operations may take, what network latency to expect, or how expensive logging could become at high request volume. It treats these values as... -
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TorchCode
Practice implementing softmax, attention, GPT-2 and more
TorchCode is an interactive learning and practice platform designed to help developers master PyTorch by implementing core machine learning operations and architectures from scratch. 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,...
