Search Results for "optimization"
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Showing 95 open source projects for "optimization"
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The NLopt module for Julia
Package to call the NLopt nonlinear-optimization library from Julia
This module provides a Julia-language interface to the free/open-source NLopt library for nonlinear optimization. NLopt provides a common interface for many different optimization algorithms. -
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Nevergrad
A Python toolbox for performing gradient-free optimization
Nevergrad is a Python library for derivative-free optimization, offering robust implementations of many algorithms suited for black-box functions (i.e. functions where gradients are unavailable or unreliable). It targets hyperparameter search, architecture search, control problems, and experimental tuning—domains in which gradient-based methods may fail or be inapplicable. The library provides an easy interface to define an optimization problem (parameter space, loss function, budget) and then experiment with multiple strategies—evolutionary algorithms, Bayesian optimization, bandit methods, genetic algorithms, etc. ... -
3
Theseus
A library for differentiable nonlinear optimization
...Theseus bridges the gap between classical optimization and deep learning, enabling hybrid systems that learn components. -
4
CasADi
CasADi is a symbolic framework for numeric optimization
CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT, etc. It can be used in C++, Python, or Matlab/Octave. CasADi's backbone is a symbolic framework implementing forward and reverse modes of AD on expression graphs to construct gradients, large-and-sparse Jacobians, and Hessians. ... -
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BayesianOptimization
A Python implementation of global optimization with gaussian processes
BayesianOptimization is a Python library that helps find the maximum (or minimum) of expensive or unknown objective functions using Bayesian optimization. This technique is especially useful for hyperparameter tuning in machine learning, where evaluating the objective function is costly. The library provides an easy-to-use API for defining bounds and optimizing over parameter spaces using probabilistic models like Gaussian Processes. -
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SciPy
SciPy library main repository
This is the main repository for the SciPy library, one of the core packages that make up the SciPy stack. SciPy is an open source software used in the fields of mathematics, science, and engineering, with modules for statistics, optimization, integration, linear algebra, signal and image processing, and many more. The SciPy library contains many of the user-friendly and efficient numerical routines, including those for numerical integration, interpolation, and optimization. SciPy is built to work with NumPy, a software that provides convenient and fast N-dimensional array manipulation. ... -
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claude-code-best-practice
Practice made claude perfect
...It also explores operational concerns such as permissions management, sandboxing, debugging workflows, and context optimization. By combining conceptual guidance with concrete examples and configuration patterns, the project helps teams move from experimental AI usage toward more production-ready agent orchestration. -
8
Binaryen
Compiler infrastructure and toolchain library for WebAssembly
...It accepts input in WebAssembly-like form but also accepts a general control flow graph for compilers that prefer that. Binaryen's internal IR uses compact data structures and is designed for completely parallel codegen and optimization, using all available CPU cores. Binaryen's IR also compiles down to WebAssembly extremely easily and quickly because it is essentially a subset of WebAssembly. Binaryen's optimizer has many passes (see an overview later down) that can improve code size and speed. These optimizations aim to make Binaryen powerful enough to be used as a compiler backend by itself. -
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Anomalib
An anomaly detection library comprising state-of-the-art algorithms
...Its design supports unsupervised or semi-supervised paradigms, making it especially powerful for scenarios where only “normal” data is readily available and defects must be detected without exhaustive labeling. Combined with its CLI and integration with optimization tools like OpenVINO, it’s suitable for both research and edge deployment tasks. -
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10
RLax
Library of JAX-based building blocks for reinforcement learning agents
...RLax is fully JIT-compilable with JAX, enabling high-performance execution across CPU, GPU, and TPU backends. The library implements tools for Bellman equations, return distributions, general value functions, and policy optimization in both continuous and discrete action spaces. It integrates seamlessly with DeepMind’s Haiku (for neural network definition) and Optax (for optimization), making it a key component in modular RL pipelines. -
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Yoast WordPress SEO
Yoast SEO for WordPress
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TBOX
A glib-like multi-platform c library
TBOX is a glib-like cross-platform C library that is simple to use yet powerful in nature. The project focuses on making C development easier and provides many modules (.e.g stream, coroutine, regex, container, algorithm ...), so that any developer can quickly pick it up and enjoy the productivity boost when developing in C language. It supports the following platforms: Windows, Macosx, Linux, Android, iOS, BSD and etc. Supports file, data, http and socket source. Supports the stream filter... -
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Manifolds.jl
Manifolds.jl provides a library of manifolds
Package Manifolds.jl aims to provide both a unified interface to define and use manifolds as well as a library of manifolds to use for your projects. This package is mostly stable, see #438 for planned upcoming changes. The implemented manifolds are accompanied by their mathematical formulae. The manifolds are implemented using the interface for manifolds given in ManifoldsBase.jl. You can use that interface to implement your own software on manifolds, such that all manifolds based on that... -
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DeepSeed
Deep learning optimization library making distributed training easy
DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. DeepSpeed delivers extreme-scale model training for everyone, from data scientists training on massive supercomputers to those training on low-end clusters or even on a single GPU. Using current generation of GPU clusters with hundreds of devices, 3D parallelism of DeepSpeed can efficiently train deep learning models with trillions of parameters. -
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Tunix
A JAX-native LLM Post-Training Library
...It embraces JAX’s strengths—functional programming, jit compilation, and effortless multi-device execution—so experiments scale from a single GPU to pods of TPUs with minimal code changes. The library is organized around modular pipelines for data loading, rollout, optimization, and evaluation, letting practitioners swap components without rewriting the whole stack. Examples and reference configs demonstrate end-to-end runs for common model families, helping teams reproduce baselines before customizing. Tunix also leans into research ergonomics: logging, checkpointing, and metrics are built in, and the code is written to be hackable rather than monolithic. ... -
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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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es-utils
ElasticSearch Utilities
es-utils is a collection of command-line utilities designed to simplify the monitoring and management of Elasticsearch clusters. It provides tools for searching, monitoring, and maintaining Elasticsearch indices, making cluster administration more efficient. -
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Windows 11 Guide
Windows Security tools, Encryption, Nextcloud, Graphics, Gaming
Windows 11 Guide is a comprehensive, single-repository handbook for setting up and tuning a Windows 11 (and often Windows 10) desktop for real day-to-day use, covering everything from basic configuration to advanced development and gaming scenarios. It walks users through installing essential applications, configuring Windows security tools, setting up encryption and backups, and integrating productivity services like Nextcloud. The guide also dives into graphics and gaming optimizations,... -
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Gonum
Set of numeric libraries for the Go programming language
Gonum is a set of numeric libraries for the Go programming language. It contains libraries for matrices, statistics, optimization, and more. Gonum is a set of packages designed to make writing numerical and scientific algorithms productive, performant, and scalable. Gonum contains libraries for matrices and linear algebra; statistics, probability distributions, and sampling; tools for function differentiation, integration, and optimization; network creation and analysis; and more. ... -
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rtabmap
RTAB-Map library and standalone application
...When a loop closure hypothesis is accepted, a new constraint is added to the map’s graph, then a graph optimizer minimizes the errors in the map. A memory management approach is used to limit the number of locations used for loop closure detection and graph optimization so that real-time constraints on large-scale environments are always respected. RTAB-Map can be used alone with a handheld Kinect, a stereo camera or a 3D lidar for 6DoF mapping, or on a robot equipped with a laser rangefinder for 3DoF mapping. -
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Axon
Nx-powered Neural Networks
...Functional API – A low-level API of numerical definitions (defn) of which all other APIs build on. Model Creation API – A high-level model creation API which manages model initialization and application. Optimization API – An API for creating and using first-order optimization techniques based on the Optax library. Training API – An API for quickly training models, inspired by PyTorch Ignite. Axon provides abstractions that enable easy integration while maintaining a level of separation between each component. You should be able to use any of the APIs without dependencies on others. ... -
22
PowerGlitch
Tiny JS library to glitch anything on the web
PowerGlitch is a standalone library with no external dependencies. It leverages CSS animations to glitch anything on the web, without using a canvas. It weights less than 2kb minified and gzipped. -
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CGAL
The Computational Geometry Algorithms Library
CGAL or the Computational Geometry Algorithms Library is a C++ library that gives you easy access to a myriad of efficient and reliable geometric algorithms. These algorithms are useful in a wide range of applications, including computer aided design, robotics, molecular biology, medical imaging, geographic information systems and more. CGAL features a great range of data structures and algorithms, including Voronoi diagrams, cell complexes and polyhedra, triangulations, arrangements of... -
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Chumsky
Write expressive, high-performance parsers with ease.
Chumsky is a parser library for Rust that focuses on expressiveness and performance. It provides developers with tools to write high-performance parsers using combinators, suitable for a wide range of parsing tasks. -
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MathPHP
Powerful modern math library for PHP
Math PHP is a library that brings advanced mathematical functions and data analysis capabilities to PHP applications. It covers a wide range of topics, including linear algebra, calculus, statistics, probability, and numerical analysis. Math PHP is designed for developers and data scientists who require precise and efficient mathematical computations in PHP, making it suitable for scientific computing and data processing.