Search Results for "optimization" - Page 5
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Showing 1192 open source projects for "optimization"
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Your monitoring isn't a stack. It's a pile. Fix that.Replace Datadog, New Relic, and Sentry without adding three more dashboards.
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CopyTranslator
Foreign language reading and translation assistant
Copy-and-translate foreign language assisted reading and translation solution. Just copy the text to the clipboard, you can view the translation results in the next second. Solve the problem of garbled codes caused by redundant sentence breaks and line breaks, and the translation results are more in line with reading habits. Infinitely close to the system-level open source implementation of translating, drag and drop to select and copy the translation. With the update of CopyTranslator, the... -
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Freqtrade
Free, open source crypto trading bot
...Example strategies to inspire you are available in the strategy repository. Download historical data of the exchange and the markets you may want to trade with. Find the best parameters for your strategy using hyper optimization which employs machining learning methods. -
3
xLUA
xLua is a lua programming solution for C#
...The most representative of these aspects are C# implementation (methods, operators, attributes, events, etc.) can be replaced with Lua implementation at runtime; excellent GC optimization, custom struct, enumeration transfer between Lua and C# without C# gc alloc; and there is no need to generate code under the editor, and the development is lighter. Open the zip package, and you will see an Assets directory, which corresponds to the Assets directory of the Unity project. Keep this directory structure and put it in your Unity project. ... -
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fe-advanced-interview
A Guide to Advanced Front-End Interviews
fe-advanced-interview is a comprehensive front-end engineering interview preparation repository focused on advanced web development concepts, system design, and real-world technical problem solving. The project compiles high-level interview questions and explanations covering JavaScript internals, browser rendering, networking, performance optimization, frameworks, architecture, and engineering best practices. Unlike beginner-focused interview guides, it emphasizes deeper understanding of how front-end technologies work internally and how large-scale applications are designed and maintained. The repository is structured as a learning resource for experienced developers preparing for senior engineering interviews at major technology companies. ... -
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GEO Content Writer
Backlog-row-first content production system for teams
...The tool is particularly useful for businesses targeting local markets or region-specific audiences. It integrates into broader SEO pipelines, allowing content generation to be part of a continuous optimization process. Overall, GEO Content Writer enables scalable, AI-driven content creation tailored for modern search ecosystems. -
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dive-into-llms
"Dive into LLMs" series of practical programming tutorials
...It includes code samples, tutorials, and conceptual breakdowns that bridge the gap between academic research and real-world implementation. The project also highlights best practices for working with LLMs, including prompt design and optimization strategies. By focusing on clarity and depth, it serves as both a teaching tool and a reference for developers. Overall, dive-into-llms provides a structured and practical approach to mastering modern language model technology. -
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J2CL
Java to Closure JavaScript transpiler
...It allows developers to write applications in Java while targeting web environments, enabling strong type safety and code reuse across platforms. Unlike monolithic frameworks, J2CL focuses purely on transpilation, leaving optimization, bundling, and runtime concerns to the broader toolchain, which provides flexibility in modern development workflows. The generated JavaScript is fully type-safe and can be aggressively optimized by the Closure Compiler to reduce code size and improve performance. J2CL is widely used internally at Google in large-scale applications such as Gmail and Google Docs, demonstrating its production readiness and scalability. ... -
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xiaohongshu-ops
Turn Openclaw into a Xiaohongshu operations assistant
xiaohongshu-ops-skill is a curated repository focused on operational strategies, growth techniques, and content optimization practices for the Xiaohongshu platform, also known as RED, which is widely used for social commerce and influencer marketing. Unlike traditional software projects, it functions as a structured knowledge base that compiles actionable insights for content creators, marketers, and businesses aiming to grow their presence on the platform. -
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Andrew NG Notes Collection
This is Andrew NG Coursera Handwritten Notes
Andrew-NG-Notes is a repository that provides comprehensive study notes for Andrew Ng’s widely known machine learning course. The project summarizes the key topics covered in the course, including supervised learning, neural networks, optimization algorithms, and model evaluation techniques. The notes aim to simplify complex mathematical explanations by organizing concepts into clear sections with diagrams, formulas, and concise descriptions. Each chapter mirrors the structure of the course curriculum, allowing students to review the material in a systematic way while following along with the lectures. ... -
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Deep Learning Interviews book
Hundreds of fully solved job interview questions
...The project was created to help students, researchers, and engineers prepare for machine learning and deep learning interviews by providing structured explanations of key concepts. The repository organizes problems across topics such as neural networks, optimization, probabilistic models, and mathematical foundations of machine learning. Each question is accompanied by detailed solutions that explain the reasoning behind the answers and the theoretical concepts involved. In addition to interview preparation, the material also serves as a condensed overview of many core topics taught in graduate-level machine learning programs. -
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All-in-RAG
Big Model Application Development Practice 1
...It explains the full development pipeline required to create knowledge-aware AI assistants, including data preparation, document indexing, vector embedding generation, and retrieval strategies. The project also explores advanced topics such as hybrid retrieval methods, query optimization, and evaluation techniques for improving system accuracy. Alongside theoretical explanations, the repository includes hands-on exercises and example projects that demonstrate how to build production-ready RAG systems. These projects guide developers through the process of integrating vector databases, embedding models, and large language models into a unified application. -
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Steam Deck Guide
Learn all about the Tools, Accessories, Games, Emulators
The Steam Deck Guide repository is a community-driven resource aimed at helping users get the most out of their Valve Steam Deck — covering everything from initial configuration and system tweaks to performance optimization, emulation workflows, game compatibility, and hardware customization. It begins with basic setup topics like installing updates, connecting peripherals, and configuring SteamOS settings, then progresses into intermediate skills such as managing storage, optimizing battery life, and fine-tuning performance profiles for demanding titles. ... -
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TechCPP
C++ learning and interview guide aimed at back-end systems developers
...It gathers frequently asked concepts and deep dives—value categories (lvalue/rvalue), perfect forwarding, casts, memory models, atomics, and more—into a structured, readable format. The material goes beyond syntax to discuss performance, optimization techniques, and how standard library containers are implemented under the hood. You’ll also find practical debugging and tooling advice, such as using gdb to diagnose deadlocks or reasoning about concurrency primitives. The repository organizes topics so you can quickly locate weak spots before interviews or brush up for day-to-day coding. ... -
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Deep Learning Is Nothing
Deep learning concepts in an approachable style
Deep-Learning-Is-Nothing presents deep learning concepts in an approachable, from-scratch style that demystifies the stack behind modern models. It typically begins with linear algebra, calculus, and optimization refreshers before moving to perceptrons, multilayer networks, and gradient-based training. Implementations favor small, readable examples—often NumPy first—to show how forward and backward passes work without depending solely on high-level frameworks. Once the fundamentals are clear, the material extends to CNNs, RNNs, and attention mechanisms, explaining why each architecture suits particular tasks. ... -
15
MemU
MemU is an open-source memory framework for AI companions
...Full proprietary features, commercial usage rights, and white-labeling options for your enterprise needs. SSO/RBAC integration and a dedicated algorithm team for scenario-specific optimization. User behavior analysis, real-time monitoring, and automated agent optimization tools. 24/7 dedicated support team, custom SLAs, and professional implementation services. -
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Pruna AI
Pruna is a model optimization framework built for developers
Pruna is an open-source, self-hostable AI inference engine designed to help teams deploy and manage large language models (LLMs) efficiently across private or hybrid infrastructures. Built with performance and developer ergonomics in mind, Pruna simplifies inference workflows by enabling multi-model orchestration, autoscaling, GPU resource allocation, and compatibility with popular open-source models. It is ideal for companies or teams looking to reduce reliance on external APIs while... -
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NVIDIA Profile Inspector
Modify game profiles inside the internal driver database
NVIDIA Profile Inspector is a specialized utility that allows users to view and modify hidden graphics driver settings within NVIDIA’s internal profile database, providing deeper control than the official NVIDIA Control Panel. It exposes advanced and undocumented configuration options that can influence rendering behavior, performance optimization, and compatibility for specific games. Users can create, edit, and assign profiles for individual applications, enabling fine-grained tuning of GPU behavior beyond standard settings. The tool is particularly popular among enthusiasts who want to optimize performance, troubleshoot graphical issues, or enable experimental features such as custom DLSS configurations. ... -
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Avogadro 2
Avogadro libraries provide 3D rendering, visualization, and analysis
AvogadroLibs is the core C++ library behind Avogadro 2, an open-source molecular editor and visualization platform used in chemistry, materials science, and education. It provides the essential tools for constructing, analyzing, and visualizing molecular structures in 2D and 3D. Designed for extensibility, AvogadroLibs supports plugins for quantum chemistry computations, molecular mechanics, and surface rendering. It interfaces with multiple chemistry formats and data sources, making it a... -
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tiny-llm
A course of learning LLM inference serving on Apple Silicon
...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. Rather than relying on high-level machine learning frameworks, the codebase uses mostly low-level array and matrix manipulation APIs so that developers can understand exactly how model inference works internally. The project demonstrates how to load and run models such as Qwen-style architectures while progressively implementing performance improvements like KV caching, request batching, and optimized attention mechanisms. ... -
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ERNIE
The official repository for ERNIE 4.5 and ERNIEKit
...It supports both full-parameter training and parameter-efficient approaches so teams can choose between maximum quality and lower-cost adaptation depending on their constraints. The project also emphasizes optimization techniques for large-scale training, including mixed-precision and hybrid-parallel strategies that are commonly needed for multi-node GPU clusters. In addition to training, it includes guidance and example materials intended to help developers adopt ERNIE models for real product scenarios rather than only research demonstrations. -
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Nano-vLLM
A lightweight vLLM implementation built from scratch
...The project recreates the core functionality of vLLM in a simplified architecture written in approximately a thousand lines of Python, making it easier for developers and researchers to understand how modern LLM inference systems work. Despite its compact design, nano-vllm incorporates advanced optimization techniques such as prefix caching, tensor parallelism, and CUDA graph execution to achieve high performance during model inference. The engine is intended primarily for educational use, experimentation, and lightweight deployments where a full production-grade inference stack may be unnecessary. Its API closely mirrors that of the original vLLM framework, allowing developers familiar with vLLM to adopt the tool with minimal changes. -
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imagor
Fast, secure image processing server and Go library, using libvips
Imagor is a fast, Docker-ready image processing server built in Go, ideal for on-the-fly image resizing, cropping, filtering, and optimization. It supports a wide variety of image formats and integrates seamlessly with cloud storage backends like AWS S3 and Google Cloud Storage. With support for HTTP and gRPC APIs, Imagor can be used in production environments to serve optimized images dynamically with high performance and low latency. -
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ReDex
A bytecode optimizer for Android apps
ReDex is an Android bytecode (dex) optimizer originally developed at Facebook. It provides a framework for reading, writing, and analyzing .dex files, and a set of optimization passes that use this framework to improve the bytecode. An APK optimized by ReDex should be smaller and faster than its source. Redex provides a framework for reading, writing, and analyzing .dex files, and a set of optimization passes that use this framework to improve the bytecode. An APK optimized by Redex should be smaller and faster. ... -
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LiteRT
LiteRT, successor to TensorFlow Lite
LiteRT is Google's next-generation on-device machine learning framework and the successor to TensorFlow Lite, designed for high-performance AI and generative AI deployment across edge devices. It provides efficient model conversion, optimization, and runtime execution while leveraging hardware acceleration from CPUs, GPUs, and NPUs. LiteRT supports a wide range of platforms, including Android, iOS, Linux, macOS, Windows, web environments, and IoT devices. The framework simplifies on-device AI development through automated accelerator selection, asynchronous execution, and optimized memory handling. ... -
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Future AGI
Open-source platform for evaluating, observing, and improving LLM
Future AGI is an open-source, end-to-end platform for evaluating, observing, protecting, and improving AI agent applications. It is built for teams that need more than basic tracing, combining evaluations, simulations, datasets, guardrails, gateway routing, and optimization in one feedback loop. The platform helps developers detect hallucinations, measure agent quality, monitor production behavior, and use evaluation results to improve prompts or workflows over time. It supports both cloud and self-hosted deployment models, making it useful for teams with different privacy, infrastructure, and compliance needs. ...
