Search Results for "users"
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205 projects for "users" with 2 filters applied:
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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Grey Wolf Optimizer for Path Planning
Grey Wolf Optimizer (GWO) path planning/trajectory
...The tool provides built-in functions to configure different UAV environments and supports multiple optimization objectives. It includes progress visualization to help monitor the optimization process during simulations. Users can adjust objective function weights and experiment with multiple heuristic search strategies to explore optimal solutions. This project demonstrates applications in multi-agent and multi-UAV cooperative path planning, making it useful for research and educational purposes in the field of intelligent optimization and robotics. -
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trackers
Multi-object tracking algorithms
...It supports inputs such as videos, webcams, RTSP streams, or image directories and produces annotated tracking outputs that include labels and trajectories. Trackers is built for flexibility and benchmarking, allowing users to evaluate performance using standard multi-object tracking metrics and compare algorithms easily. Its architecture emphasizes interoperability so developers can combine their preferred detection models with different trackers without rewriting core logic. -
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PRML
PRML algorithms implemented in Python
...Rather than just summarizing concepts, the repository includes working code that demonstrates linear regression and classification, kernel methods, neural networks, graphical models, mixture models with EM algorithms, approximate inference, and sequential data methods — all following the book’s structure and notation. Many of these algorithms are paired with Jupyter notebooks that let users interact with the code, visualize results, and experiment with parameters in a way that deeply strengthens theoretical understanding. -
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Pythonic Data Structures and Algorithms
Minimal examples of data structures and algorithms in Python
The Pythonic Data Structures and Algorithms repository by keon is a hands-on collection of implementations of classical data structures and algorithms written in Python. It offers working, often well-commented code for many standard algorithmic problems — from sorting/searching to graph algorithms, dynamic programming, data structures, and more — making it a valuable resource for learning and reference. For students preparing for technical interviews, self-learners brushing up on... -
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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Armadillo
fast C++ library for linear algebra & scientific computing
* Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. * Downloads:... -
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RHash (Recursive Hasher) is a console utility for computing and verifying hash sums of files. It supports CRC32, CRC32C, MD4, MD5, SHA1, SHA256, SHA512, SHA3, AICH, ED2K, DC++ TTH, BTIH, Tiger, GOST R 34.11-2012, RIPEMD-160, HAS-160, EDON-R, and Whirlpool.
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Java·Applied·Geodesy·3D
Least-Squares Adjustment Software for Geodetic Sciences
JAG3D is no longer developed at source-forge, and has moved to GitHub. Please visit https://github.com/applied-geodesy/jag3d or https://software.applied-geodesy.org to get the latest version. -
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Evolutionary Computation Framework
C++ framework for application of any type of evolutionary computation.
ECF is a framework intended for application of any type of evolutionary computation (GA/GP, DE, Clonalg, ES, PSO, ABC, GAn, local search...). It offers simplicity for the end-user (parameterless usage, tutorial) and customization for experienced EC practicioners. -
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Bandicoot
fast C++ library for GPU linear algebra & scientific computing
* Fast GPU linear algebra library (matrix maths) for the C++ language, aiming towards a good balance between speed and ease of use * Provides high-level syntax and functionality deliberately similar to Matlab * Provides an API that is aiming to be compatible with Armadillo for easy transition between CPU and GPU linear algebra code * Useful for algorithm development directly in C++, or quick conversion of research code into production environments * Distributed under the permissive... -
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MOA - Massive Online Analysis
Big Data Stream Analytics Framework.
A framework for learning from a continuous supply of examples, a data stream. Includes classification, regression, clustering, outlier detection and recommender systems. Related to the WEKA project, also written in Java, while scaling to adaptive large scale machine learning. -
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Adaptive Simulated Annealing (ASA)
simulated annealing optimization and importance-sampling
Adaptive Simulated Annealing (ASA) is a C-language code that finds the best global fit of a nonlinear cost-function over a D-dimensional space. ASA has over 100 OPTIONS to provide robust tuning over many classes of nonlinear stochastic systems. -
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Evolutionary Algorithm
Evolutionary Algorithm using Python
...Rather than being a single monolithic library, this repository provides a series of self-contained examples showing how different population-based search methods solve optimization problems and adapt candidate solutions over generations. Users can explore basic genetic algorithm setups, match phrase examples, pathfinding challenges, and microbial GA variants, as well as evolution strategy approaches like NES. The project also links classical evolutionary approaches with neural networks, illustrating how evolution can be used for model training in reinforcement learning and supervised contexts. -
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antigift
antigift is simple cross-platform, files & folders encryption tool
antigift could be used for encryption files & folders on USB-flash or HDD partition. Works on Linux (including Android), Windows, Mac OS X, FreeBSD, DragonFly BSD and other on OSes. Do not required installation. Include WIPE tool for wiping free space and tool for recovery forgotten key. See documentation at http://sourceforge.net/p/antigift/wiki/Home/ antigift простой и кросс-платформенный инструмент для шифрования файлов и папок(с ccrypt в качестве основы) Подробности см. на... -
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MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
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DuranDuranbot
Teachable/trainable artificially intelligent music bot
A teachable/trainable artificially intelligent music bot fundamentally inspired by how the new wave band Duran Duran composes music. This program utilizes many algorithmic/AI techniques/processes, including machine learning; which allow you to teach/train it to compose music which you prefer... and the technique which is the foundation of the design of DuranDuranbot, which was directly inspired by how Duran Duran writes music........ Called, "bit by bit circular composition"....... and it's... -
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Sudoku Maker is a generator for Sudoku number puzzles. It uses a genetic algorithm internally, so it can serve as an introduction to genetic algorithms. The generated Sudokus are usually very hard to solve -- good for getting rid of a Sudoku addiction.
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Reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI
...The project collects popular approaches such as dynamic programming, Monte Carlo methods, temporal difference learning, Q-learning, SARSA, deep Q-networks, and policy gradient techniques, often demonstrated with Python and OpenAI Gym environments so users can experiment with agents learning in simulated tasks. For each algorithm category, the repository pairs conceptual descriptions with runnable code and often illustrated exercises that help solidify understanding by bridging theory with practice. It’s structured to serve learners progressing from basic tabular methods to function approximation and deep learning extensions, making it suitable for students, researchers, or practitioners exploring reinforcement learning fundamentals. -
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scikit-opt
Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing
...It includes genetic algorithms, particle swarm optimization, differential evolution, simulated annealing, ant colony optimization, immune algorithms, and artificial fish swarms. The package can address continuous objectives, constrained problems, and combinatorial tasks such as the traveling salesman problem. A consistent workflow lets users define an objective, configure an optimizer, run iterations, and inspect the best solution. Genetic algorithm operators can be replaced through user-defined functions or subclassing. Runs may continue from earlier iterations instead of restarting. Vectorization, threading, multiprocessing, caching, examples, and plotting support help users experiment with performance and convergence. -
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lpsolve
Mixed Integer Linear Programming (MILP) solver.
Mixed Integer Linear Programming (MILP) solver lp_solve solves pure linear, (mixed) integer/binary, semi-cont and special ordered sets (SOS) models.lp_solve is written in ANSI C and can be compiled on many different platforms like Linux and WINDOWS This project is moved to github: https://lp-solve.github.io/ -
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This project hosts a library and tools for sharing simulation experiments encoded using SED-ML.
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ExRandom
Sampling exactly from the normal and exponential distributions
ExRandom is a small header-only C++11 library for exact sampling from the normal, exponential, and discrete normal distributions (provided that the underlying generator is perfect). This library provides an implementation of the algorithms described in C. F. F. Karney, Sampling exactly from the normal distribution, ACM Trans. Math. Software 42(1), 3:1-14 (Jan. 2016), https://doi.org/10.1145/2710016, https://arxiv.org/abs/1303.6257. -
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Base62 Encode/Decode Utility
A tool for encoding/decoding to base62
the package chewingum contains two main programs: - base62 - chew They have been implemented in perl. Base62 has been coded in c++ too. chew has been written to shorten long decimal integer numbers into base62 strings. It's not a mere base conversion, because it doesn't use arithmetic inside its logic. In this way it can convert very long numbers into strings quickly, without overflows. For example if I want to share an id using an url, this will make the url shorter. the... -
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C-squares
Concise spatial query and representation system (c-squares)
C-squares is an easily implemented method for storage, querying and display of spatial data locations, based on a hierarchical, grid-based representation of the Earth' surface. Source code for encoding, decoding, mapping, etc. is provided via this site. Additional support is available by contacting the system developer, Tony.Rees@marinespecies.org; see also the c-squares home page at http://www.cmar.csiro.au/csquares/ . -
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PythonRobotics
Python sample codes and textbook for robotics algorithms
...The project is written to make each algorithm’s core idea easy to understand, rather than hiding the logic behind large frameworks. It keeps dependencies minimal so learners can focus on the math, implementation, and behavior of each robotics method. Visual examples and simulations help users see how algorithms move, estimate, plan, and react. PythonRobotics is especially useful for students, researchers, and engineers who want a hands-on reference for robotics fundamentals in Python.
