Search Results for "course allocation system"
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Showing 252 open source projects for "course allocation system"
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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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Codebase to Course
A Claude Code skill that turns any codebase into an HTML course
Codebase to Course is an AI-powered development tool that converts any software repository into a fully interactive educational experience presented as a self-contained HTML course. It is implemented as a skill for Claude Code and is designed to help users understand how a codebase works without requiring a formal computer science background. The tool analyzes the structure and behavior of a project and generates a visually rich, scroll-based course that includes diagrams, animations, and... -
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System Design
Learn how to design systems and prepare for system design interviews
This project is an open, course-style repository designed to help you learn system design from fundamentals through advanced, interview-ready thinking. It organizes core networking and distributed-systems concepts into a structured path, so you can build intuition before jumping into “design X” exercises. It covers the building blocks that show up in real architectures, such as DNS, load balancing, caching, CDNs, proxies, scalability and availability tradeoffs, and storage patterns, then connects those pieces to larger system goals. ... -
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OmniGet
Udemy & Hotmart course downloader, YouTube downloader
...A large built-in toolbox covers media, files, system utilities, OCR, conversion, and other workflows. Plugins add course study, Telegram access, media conversion, notes, flashcards, and related features. OmniGet is free, open source, and available for Windows, macOS, and Linux. -
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second-brain-ai-assistant-course
Learn to build your Second Brain AI assistant with LLMs
The Second Brain AI Assistant Course is an open-source educational project designed to teach developers how to build a personal AI assistant that interacts with a user’s knowledge base. The course provides a structured curriculum that walks learners through the architecture and implementation of a production-ready AI system powered by large language models. The concept of a “second brain” refers to a personal knowledge repository containing notes, research, and documents that can be queried and analyzed using AI. ... -
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SpaceWasm
A flight-compliant WebAssembly interpreter
...A streaming decoder reads modules in chunks, validates them in one pass, and converts instructions into an interpretation-focused intermediate representation. Its custom memory model uses fixed-size pages to provide deterministic allocation behavior and avoid panic on allocation failure. Embedders can expose controlled host functions while restricting program access, compute time, and system interactions. The project emphasizes sandboxing, portability, predictable resource use, and compatibility with flight-software requirements. Tests, fuzzing, benchmarks, requirements, and integration components are included in the Rust codebase. -
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OriLauncher
Fast, user-friendly cross-platform custom launcher for Minecraft
...It also offers support for managing multiple user accounts, remembering both Microsoft and offline profiles to make logging in simpler and more fluid. Players have control over technical settings like RAM allocation and Java version selection directly within the launcher, allowing them to optimize performance for their system. -
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Brook
Brook is a cross-platform strong encryption and not detectable proxy
Brook is a cross-platform strong encryption and not detectable proxy. Brook's goal is to keep it simple, stupid and not detectable. You can run commands after entering the command-line interface. Usually, everyone uses the command line interface on Linux servers. Of course, Linux also has desktops that can also run GUI. Of course, macOS and Windows also have command-line interfaces, but you may not use them frequently. Usually, the applications opened by double-clicking/clicking on... -
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The Bitdefender disassembler
bddisasm is a fast, lightweight, x86/x64 instruction decoder
The Bitdefender disassembler is a highly optimized, lightweight x86/x64 instruction decoder designed for security, reverse engineering, and low-level systems analysis. It focuses on decoding machine instructions with high precision while providing detailed metadata about each instruction, including operands, access modes, CPU flags, and feature requirements. Unlike many disassemblers, bddisasm is built with zero dynamic memory allocation and no external dependencies, making it extremely... -
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QDirStat
Qt-based directory statistics
Qt-based directory statistics: KDirStat without any KDE -- from the author of the original KDirStat. QDirStat is a graphical application to shows where your disk space has gone and to help you to clean it up. This is a Qt-only port of the old Qt3/KDE3-based KDirStat, now based on the latest Qt 5. It does not need any KDE libs or infrastructure. It runs on every X11-based desktop on Linux, BSD and other Unix-like systems and of course in a Docker container. -
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RemixIcon
Open source neutral style icon system
Remix Icon is a set of open-source neutral-style system symbols for designers and developers. Unlike a patchwork icon library, 2400+ icons are all elaborately crafted so that they are born with the gene of readability, consistency and perfect pixels. Each icon was designed in "Outlined" and "Filled" styles based on a 24x24 grid. Of course, all the icons are free for both personal and commercial use. -
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TensorFlow Lite for Microcontrollers
Infrastructure to enable deployment of ML models
...It targets microcontrollers, DSPs, and other resource-constrained hardware where memory, compute, and power are limited. The project enables on-device inference without depending on an operating system, standard C or C++ libraries, or dynamic memory allocation. It is useful for applications such as wake-word detection, sensor analysis, gesture recognition, anomaly detection, and small vision or audio models. Developers can train or convert models into TensorFlow Lite format and deploy them into embedded firmware. Its main value is bringing practical machine learning to edge devices that are too small for conventional mobile or server runtimes. -
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os-tutorial
How to create an OS from scratch
os-tutorial is an open source educational project by cfenollosa that teaches the basics of building an operating system from scratch. The repository provides step-by-step lessons starting with bootloaders and moving through kernel development, interrupts, memory management, and system calls. Each tutorial is accompanied by clear explanations, code examples, and references to deepen understanding. The project uses x86 assembly and C to illustrate concepts, making it accessible to students and... -
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ClawTeam
ClawTeam: Agent Swarm Intelligence (One Command → Full Automation)
ClawTeam is an advanced multi-agent orchestration framework that enables AI agents to form collaborative swarms capable of solving complex tasks autonomously. Instead of relying on a single agent, the system allows a leader agent to spawn and coordinate multiple specialized sub-agents, each responsible for different aspects of a problem. These agents communicate, share insights, and dynamically adapt their strategies based on real-time feedback, creating a form of collective intelligence.... -
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ioredis
A performance-focused Redis client for Node.js
ioredis is a robust, full-featured Redis client that is used in the world's biggest online commerce company Alibaba and many other awesome companies. Full-featured. It supports Cluster, Sentinel, Streams, Pipelining and of course Lua scripting & Pub/Sub (with the support of binary messages). High performance. Delightful API. It works with Node callbacks and Native promises. Transformation of command arguments and replies. Transparent key prefixing. Abstraction for Lua scripting, allowing you... -
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tiny-llm
A course of learning LLM inference serving on Apple Silicon
tiny-llm is an educational open-source project designed to teach system engineers how large language model inference and serving systems work by building them from scratch. The project is structured as a guided course that walks developers through the process of implementing the core components required to run a modern language model, including attention mechanisms, token generation, and optimization techniques. -
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django-health-check
a pluggable app that runs a full check on the deployment
The primary intended use case is to monitor conditions via HTTP(S), with responses available in HTML and JSON formats. When you get back a response that includes one or more problems, you can then decide the appropriate course of action, which could include generating notifications and/or automating the replacement of a failing node with a new one. If you are monitoring health in a high-availability environment with a load balancer that returns responses from multiple nodes, please note that... -
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Chez Scheme
A programming language and an implementation of that language
Chez Scheme is both a programming language and an implementation of that language, with supporting tools and documentation. As a superset of the language described in the Revised6 Report on the Algorithmic Language Scheme (R6RS), Chez Scheme supports all standard features of Scheme, including first-class procedures, proper treatment of tail calls, continuations, user-defined records, libraries, exceptions, and hygienic macro expansion. The Chez Scheme implementation consists of a compiler,... -
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Fairlearn
A Python package to assess and improve fairness of ML models
Fairlearn is a Python package that empowers developers of artificial intelligence (AI) systems to assess their system's fairness and mitigate any observed unfairness issues. Fairlearn contains mitigation algorithms as well as metrics for model assessment. Besides the source code, this repository also contains Jupyter notebooks with examples of Fairlearn usage. An AI system can behave unfairly for a variety of reasons. In Fairlearn, we define whether an AI system is behaving unfairly in terms... -
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MemGuard
Secure software enclave for storage of sensitive information in memory
...It aims to support all major operating systems and is written in pure Go. Sensitive data is encrypted and authenticated in memory with XSalsa20Poly1305. The scheme used also defends against cold-boot attacks. Memory allocation bypasses the language runtime by using system calls to query the kernel for resources directly. This avoids interference from the garbage collector. Buffers that store plaintext data are fortified with guard pages and canary values to detect spurious accesses and overflows. The effort is taken to prevent sensitive data from touching the disk. ... -
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Discovery
Nepxion Discovery is a solution for Spring Cloud
Nepxion Discovery is a solution for Spring Cloud with blue green, gray, route, blacklist, limitation, circuit breaker, degrade, isolation, monitor, tracing, dye, failover, async agent. Only one or more services are upgraded at a time, the upgrade is completed and monitored and observed, and this process is performed continuously until all the old versions in the cluster are upgraded to the new version. In the process of stopping the old version, it is impossible to accurately calculate... -
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Halfrost-Field Frostland
This is the place to blog
Halfrost-Field is a large public “knowledge and blog repository” maintained by a developer who documents a wide variety of computer-science, programming, and machine-learning content — from classic algorithms, ML fundamentals, to system design and broader engineering topics. The repository is structured like a personal technical blog/book: it contains “contents” directories with Markdown-based notes, tutorials and guides. For example, there is a full machine learning course outline (regression, neural networks, SVMs, unsupervised learning, anomaly detection, large-scale ML, even application examples like OCR), that reads like a self-study curriculum. ... -
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Open Vibe
Open Vibe turns Claude Code into a SaaS-building assistant
...After creating a new Wasp app, the user opens an AI coding agent inside the project and lets it fetch course module instructions. The agent then works as both tutor and pair programmer, explaining the system while helping the user build features from plain-language requests. Progress is tracked through JSON files written into the project, making the learning path structured while still letting the user build their own app idea. -
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SameBoy
Game Boy and Game Boy Color emulator written in C
SameBoy is a user friendly, powerful and open source Game Boy, Game Boy Color and Super Game Boy emulator for macOS, Windows and Unix-like platforms. SameBoy is extremely accurate and includes a wide range of both powerful debugging features and user-facing features, making it ideal for both casual players and developers. Of course, SameBoy also has every feature one would expect from an emulator – from save states to scaling filters. Supports Game Boy (DMG), Game Boy Pocket and Light (MGB),... -
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PicoLM
Run a 1-billion parameter LLM on a $10 board with 256MB RAM
PicoLM is an open-source inference framework designed to run large language models on extremely constrained hardware environments such as inexpensive single-board computers and embedded systems. The project focuses on enabling efficient local inference by optimizing memory usage, computation, and system dependencies so that relatively large models can operate on devices with minimal RAM. It is written primarily in C and designed with a minimalist architecture that removes unnecessary... -
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ElasticJob
Distributed scheduled job framework
...ElasticJob-Cloud uses Mesos to manage and isolate resources. It uses a unified job API for each project. Developers only need code one time and can deploy at will. Support job sharding and high availability in distributed system. Scale out for throughput and efficiency improvement. Job processing capacity is flexible and scalable with the allocation of resources. Execute job on suitable time and assigned resources. Aggregation same job to same job executor. Append resources to newly assigned jobs dynamically. Using ElasticJob can make developers no longer worry about the non-functional requirements such as jobs scale out, so that they can focus more on business coding.
