Search Results for "algorithms" - Page 2
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Showing 1676 open source projects for "algorithms"
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Homemade Machine Learning
Python examples of popular machine learning algorithms
...The purpose is pedagogical: you’ll see linear regression, logistic regression, k-means clustering, neural nets, decision trees, etc., built in Python using fundamentals like NumPy and Matplotlib, not hidden behind API calls. It is well suited for learners who want to move beyond library usage to understand how algorithms operate internally—how cost functions, gradients, updates and predictions work. -
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Gen.jl
A general-purpose probabilistic programming system
An open-source stack for generative modeling and probabilistic inference. Gen’s inference library gives users building blocks for writing efficient probabilistic inference algorithms that are tailored to their models, while automating the tricky math and the low-level implementation details. Gen helps users write hybrid algorithms that combine neural networks, variational inference, sequential Monte Carlo samplers, and Markov chain Monte Carlo. Gen features an easy-to-use modeling language for writing down generative models, inference models, variational families, and proposal distributions using ordinary code. ... -
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Rubix ML
A high-level machine learning and deep learning library for PHP
...We provide tools for the entire machine learning life cycle from ETL to training, cross-validation, and production with over 40 supervised and unsupervised learning algorithms. In addition, we provide tutorials and other educational content to help you get started using ML in your projects. Our intuitive interface is quick to grasp while hiding alot of power and complexity. Write less code and iterate faster leaving the hard stuff to us. Rubix ML utilizes a versatile modular architecture that is defined by a few key abstractions and their types and interfaces. ... -
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ngraph.path
Path finding in a graph
ngraph.path is a JavaScript library that implements efficient pathfinding algorithms for graphs, primarily designed to compute shortest paths in weighted or unweighted networks. It provides a clean API for constructing graph models, assigning weights to edges, and querying for optimal routes between nodes, making it useful for routing, games, maps, and network optimization. The library includes several algorithm implementations such as A*, Dijkstra’s, and breadth-first search, each suited to different types of graph structure and performance needs. ... -
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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. ... -
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CUDA Core Compute Libraries (CCCL)
CUDA Core Compute Libraries
...The goal of CCCL is to simplify CUDA development by offering reusable building blocks that enable developers to write efficient and scalable parallel code without starting from scratch. Thrust provides a high-level interface for parallel algorithms, while CUB delivers highly optimized primitives for device-level operations, and libcudacxx ensures compatibility with modern C++ standards. By unifying these components, CCCL reduces duplication and improves developer productivity while maintaining performance across different GPU architectures. -
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FATE
An industrial grade federated learning framework
...It implements secure computation protocols based on homomorphic encryption and multi-party computation (MPC). Supporting various federated learning scenarios, FATE now provides a host of federated learning algorithms, including logistic regression, tree-based algorithms, deep learning and transfer learning. FATE became open-source in February 2019. FATE TSC was established to lead FATE open-source community, with members from major domestic cloud computing and financial service enterprises. FedAI is a community that helps businesses and organizations build AI models effectively and collaboratively, by using data in accordance with user privacy protection, data security, data confidentiality and government regulations. -
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EASTL
EASTL, Electronic Arts Standard Template Library
EASTL stands for Electronic Arts Standard Template Library. It is a C++ template library of containers, algorithms, and iterators useful for runtime and tool development across multiple platforms. It is a fairly extensive and robust implementation of such a library and has an emphasis on high performance above all other considerations. If you are familiar with the C++ STL or have worked with other templated container/algorithm libraries, you probably don't need to read this. -
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PyMC3
Probabilistic programming in Python
...Variational inference saves computational cost by turning a problem of integration into one of optimization. PyMC3's variational API supports a number of cutting edge algorithms, as well as minibatch for scaling to large datasets. -
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Open3D
A modern library for 3D data processing
Open3D is an open-source library that supports rapid development of software that deals with 3D data. The Open3D frontend exposes a set of carefully selected data structures and algorithms in both C++ and Python. The backend is highly optimized and is set up for parallelization. Open3D was developed from a clean slate with a small and carefully considered set of dependencies. It can be set up on different platforms and compiled from source with minimal effort. The code is clean, consistently styled, and maintained via a clear code review mechanism. ... -
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WindTerm
A professional cross-platform SSH/Sftp/Shell/Telnet/Serial terminal
...WindTerm is a partial open source project, and the source will be gradually opened. Open source code includes, but is not limited to, the classes that can be used independently, such as functional, algorithms, GUI widgets, etc., as well as functional libraries, such as networks, protocols, etc., as well as all types that require open source according to the license. SSH v2, Telnet, Raw TCP, Serial, Shell protocols were implemented. Supports SSH auto-execution when the session is authenticated. Integrated local file manager, supports the move to, copy to, copy from, remove, rename, make new file/directory and so on. ... -
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Recommenders 2023
Best Practices on Recommendation Systems
Recommenders objective is to assist researchers, developers and enthusiasts in prototyping, experimenting with and bringing to production a range of classic and state-of-the-art recommendation systems. Recommenders is a project under the Linux Foundation of AI and Data. -
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Avalanche
End-to-End Library for Continual Learning based on PyTorch
...This includes simple and efficient ways of implementing new continual learning strategies as well as a set of pre-implemented CL baselines and state-of-the-art algorithms you will be able to use for comparison! Avalanche the first experiment of an End-to-end Library for reproducible continual learning research & development where you can find benchmarks, algorithms, etc. -
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Machine Learning Tutorials Repository
Dive deep into the realms of Machine Learning and other topics
...The project is structured to provide both theoretical explanations and practical code examples, making it suitable for learners at different levels. It includes implementations of algorithms using popular tools and libraries, allowing users to experiment and build their own models. The repository also serves as a reference for common patterns and workflows in machine learning development. By combining educational content with hands-on examples, it bridges the gap between theory and practice. -
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shadowsocks-libev
Bug-fix-only libev port of shadowsocks
Shadowsocks-libev is a lightweight secured SOCKS5 proxy for embedded devices and low-end boxes. Shadowsocks-libev is written in pure C and depends on libev. It's designed to be a lightweight implementation of shadowsocks protocol, in order to keep the resource usage as low as possible. Snap is the recommended way to install the latest binaries. You can build shadowsocks-libev and all its dependencies by script. The latest shadowsocks-libev has provided a redir mode. You can configure your... -
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hash-wasm
Lightning fast hash functions using hand-tuned WebAssembly binaries
...It supports both simple one-shot hashing and advanced streaming modes, allowing developers to process large datasets incrementally. The architecture is modular, enabling tree-shaking so that only the required algorithms are included in the final bundle, reducing application size. -
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Image Harmonization Dataset iHarmony4
The first large-scale public benchmark dataset for image harmonization
This repository provides the iHarmony4 dataset, which is a large-scale dataset designed for image harmonization tasks. Image harmonization involves adjusting the appearance of a foreground in a composite image so that it is consistent with the background (in color, tone, illumination, etc.). The iHarmony4 dataset comprises four sub-datasets (HCOCO, HAdobe5k, HFlickr, Hday2night), each making composite images by combining a foreground from one image with a background from another, along with... -
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RecBole
A unified, comprehensive and efficient recommendation library
...We design general and extensible data structures to unify the formatting and usage of various recommendation datasets. We implement more than 100 commonly used recommendation algorithms and provide formatted copies of 28 recommendation datasets. We support a series of widely adopted evaluation protocols or settings for testing and comparing recommendation algorithms. RecBole is developed based on Python and PyTorch for reproducing and developing recommendation algorithms in a unified, comprehensive and efficient framework for research purpose. ... -
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NetworkX
Network analysis in Python
NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. Data structures for graphs, digraphs, and multigraphs. Many standard graph algorithms. Network structure and analysis measures. Generators for classic graphs, random graphs, and synthetic networks. Nodes can be "anything" (e.g., text, images, XML records). Edges can hold arbitrary data (e.g., weights, time-series). Open source 3-clause BSD license. Well tested with over 90% code coverage. Additional benefits from Python include fast prototyping, easy to teach, and multi-platform. ... -
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mpv.net
mpv.net is a modern media player for Windows that works just like mpv
mpv.net is a modern desktop media player for Windows based on the popular mpv player. mpv.net is designed to be mpv compatible, almost all mpv features are available because they are all contained in libmpv, this means the official mpv manual applies to mpv.net. mpv focuses on the usage of the command line and the terminal, mpv.net retains the ability to be used from the command line and the terminal and adds a modern Windows GUI on top of it. Video output that is capable of many features loved by videophiles, such as video scaling with popular high-quality algorithms, color management, frame timing, interpolation, HDR, and more. Leverages the FFmpeg hwaccel APIs to support DXVA2 video decoding acceleration. mpv.net is based on libmpv which offers a straightforward C API that was designed from the ground up to make mpv usable as a library and facilitate easy integration into other applications. mpv is like VLC not based on DirectShow or Media Foundation. -
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Apache Spark
A unified analytics engine for large-scale data processing
...With Spark Streaming (microbatches) and Structured Streaming, it delivers low-latency event processing suitable for real-time analytics. The built-in MLlib library provides scalable machine learning algorithms, while GraphX enables graph computations integrated with data pipelines. Spark supports multiple languages—Scala, Java, Python, R—and connects with many storage systems like HDFS, S3, Cassandra, and streaming platforms like Kafka, making it a versatile choice for big data workloads in analytics, ETL, and data science. -
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AlphaZero.jl
A generic, simple and fast implementation of Deepmind's AlphaZero
Beyond its much publicized success in attaining superhuman level at games such as Chess and Go, DeepMind's AlphaZero algorithm illustrates a more general methodology of combining learning and search to explore large combinatorial spaces effectively. We believe that this methodology can have exciting applications in many different research areas. Because AlphaZero is resource-hungry, successful open-source implementations (such as Leela Zero) are written in low-level languages (such as C++)... -
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mold
A Modern Linker
...In compiled languages like C, C++, and Rust, the linking phase can become a significant bottleneck, especially in large codebases, and mold addresses this by leveraging highly optimized algorithms and extensive parallelism. It is capable of utilizing all available CPU cores efficiently, resulting in significantly faster linking compared to other popular linkers such as GNU ld, gold, and LLVM lld. The tool is designed to integrate seamlessly into existing build systems, requiring minimal configuration changes to adopt. Mold supports a wide range of architectures, including x86-64, ARM, RISC-V, and PowerPC, making it suitable for diverse development environments. -
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Numba
NumPy aware dynamic Python compiler using LLVM
Numba is an open source JIT compiler that translates a subset of Python and NumPy code into fast machine code. Numba translates Python functions to optimized machine code at runtime using the industry-standard LLVM compiler library. Numba-compiled numerical algorithms in Python can approach the speeds of C or FORTRAN. You don't need to replace the Python interpreter, run a separate compilation step, or even have a C/C++ compiler installed. Just apply one of the Numba decorators to your Python function, and Numba does the rest. Numba is designed to be used with NumPy arrays and functions. Numba generates specialized code for different array data types and layouts to optimize performance. ... -
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Exclusively Dark Image Dataset
ExDARK dataset is the largest collection of low-light images
The Exclusively Dark (ExDARK) dataset is one of the largest curated collections of real-world low-light images designed to support research in computer vision tasks under challenging lighting conditions. It contains 7,363 images captured across ten different low-light scenarios, ranging from extremely dark environments to twilight. Each image is annotated with both image-level labels and object-level bounding boxes for 12 object categories, making it suitable for detection and classification...
