Showing 767 open source projects for "linear"

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  • 1
    MLJAR Studio

    MLJAR Studio

    Python package for AutoML on Tabular Data with Feature Engineering

    We are working on new way for visual programming. We developed a desktop application called MLJAR Studio. It is a notebook-based development environment with interactive code recipes and a managed Python environment. All running locally on your machine. We are waiting for your feedback. The mljar-supervised is an Automated Machine Learning Python package that works with tabular data. It is designed to save time for a data scientist. It abstracts the common way to preprocess the data,...
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  • 2
    UMAP

    UMAP

    Uniform Manifold Approximation and Projection

    Uniform Manifold Approximation and Projection (UMAP) is a dimension reduction technique that can be used for visualization similarly to t-SNE, but also for general non-linear dimension reduction. It is possible to model the manifold with a fuzzy topological structure. The embedding is found by searching for a low-dimensional projection of the data that has the closest possible equivalent fuzzy topological structure. First of all UMAP is fast. It can handle large datasets and high dimensional...
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  • 3
    Tegon

    Tegon

    Tegon is an open-source, AI-first alternative to Jira, Linear

    Tegon is an AI-first, open-source issue-tracking software that uses AI to smartly automate manual tasks, and workflows or provide more context to engineers for a given task. Manual efforts in task management, such as task triaging and backlog maintenance, can be time-consuming. Engineers often lose time navigating multiple platforms to gather task context, rather than accessing details within the task itself. Issue tracking tools serve as a task database, directing engineers on what to work...
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  • 4
    AtomAI

    AtomAI

    Deep and Machine Learning for Microscopy

    AtomAI is a Pytorch-based package for deep and machine-learning analysis of microscopy data that doesn't require any advanced knowledge of Python or machine learning. The intended audience is domain scientists with a basic understanding of how to use NumPy and Matplotlib. It was developed by Maxim Ziatdinov at Oak Ridge National Lab. The purpose of the AtomAI is to provide an environment that bridges the instrument-specific libraries and general physical analysis by enabling the seamless...
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  • 5
    NonlinearSolve.jl

    NonlinearSolve.jl

    High-performance and differentiation-enabled nonlinear solvers

    ... linear solvers, along with the ability to use sparse automatic differentiation for Jacobian construction and Jacobian-vector products. NonlinearSolve.jl interfaces with other packages of the Julia ecosystem to make it easy to test alternative solver packages and pass small types to control algorithm swapping. It also interfaces with the ModelingToolkit.jl world of symbolic modeling to allow for automatically generating high-performance code.
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  • 6
    Measurements.jl

    Measurements.jl

    Error propagation calculator and library for physical measurements

    ... an attached error to quantify the confidence about its accuracy. Measurements.jl relieves you from the hassle of propagating uncertainties coming from physical measurements, when performing mathematical operations involving them. The linear error propagation theory is employed to propagate the errors.
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  • 7
    Quantum++

    Quantum++

    Modern C++ quantum computing library

    Quantum++ is a modern C++ general-purpose quantum computing library, composed solely of template header files. Quantum++ is written in standard C++17 and has very low external dependencies, using only the Eigen 3 linear algebra header-only template library and, if available, the OpenMP multiprocessing library. Quantum++ is not restricted to qubit systems or specific quantum information processing tasks, being capable of simulating arbitrary quantum processes. The main design factors taken...
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  • 8
    Automated Tool for Optimized Modelling

    Automated Tool for Optimized Modelling

    Automated Tool for Optimized Modelling

    During the exploration phase of a machine learning project, a data scientist tries to find the optimal pipeline for his specific use case. This usually involves applying standard data cleaning steps, creating or selecting useful features, trying out different models, etc. Testing multiple pipelines requires many lines of code, and writing it all in the same notebook often makes it long and cluttered. On the other hand, using multiple notebooks makes it harder to compare the results and to...
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  • 9
    StructuralEquationModels.jl

    StructuralEquationModels.jl

    A fast and flexible Structural Equation Modelling Framework

    This is a package for Structural Equation Modeling in development. It is written for extensibility, that is, you can easily define your own objective functions and other parts of the model. At the same time, it is (very) fast. We provide fast objective functions, gradients, and for some cases hessians as well as approximations thereof. As a user, you can easily define custom loss functions. For those, you can decide to provide analytical gradients or use finite difference approximation /...
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  • 10
    CoreUI Icons

    CoreUI Icons

    Premium designed free icon set with marks in SVG, Webfont and raster

    Premium-designed free icon set with marks in SVG, JavaScript, and Webfont formats. CoreUI Icons are beautifully crafted symbols for common actions and items. You can use them in your digital products for web or mobile apps. WOFF, SVG, TFF, and much more to make your development easier. Download our free package or buy pro. You gain SOLID, LINEAR and soon DUO-TONE style sets. Just browse our library to find out more. Multiple icons are grouped in categories like Nature, Transport, Interface...
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  • 11
    CUTLASS

    CUTLASS

    CUDA Templates for Linear Algebra Subroutines

    CUTLASS is a collection of CUDA C++ template abstractions for implementing high-performance matrix-multiplication (GEMM) and related computations at all levels and scales within CUDA. It incorporates strategies for hierarchical decomposition and data movement similar to those used to implement cuBLAS and cuDNN. CUTLASS decomposes these "moving parts" into reusable, modular software components abstracted by C++ template classes. These thread-wide, warp-wide, block-wide, and device-wide...
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  • 12
    mlpack

    mlpack

    mlpack: a scalable C++ machine learning library

    mlpack is an intuitive, fast, and flexible C++ machine learning library with bindings to other languages. It is meant to be a machine learning analog to LAPACK, and aims to implement a wide array of machine learning methods and functions as a "swiss army knife" for machine learning researchers. In addition to its powerful C++ interface, mlpack also provides command-line programs, Python bindings, Julia bindings, Go bindings and R bindings. Written in C++ and built on the Armadillo linear...
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  • 13
    Kornia

    Kornia

    Open Source Differentiable Computer Vision Library

    Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer vision problems. At its core, the package uses PyTorch as its main backend both for efficiency and to take advantage of the reverse-mode auto-differentiation to define and compute the gradient of complex functions. Inspired by existing packages, this library is composed by a subset of packages containing operators that can be inserted within...
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  • 14
    Cookiecutter Data Science

    Cookiecutter Data Science

    Project structure for doing and sharing data science work

    ... about bikeshedding the indentation aesthetics or pedantic formatting standards, ultimately, data science code quality is about correctness and reproducibility. It's no secret that good analyses are often the result of very scattershot and serendipitous explorations. Tentative experiments and rapidly testing approaches that might not work out are all part of the process for getting to the good stuff, and there is no magic bullet to turn data exploration into a simple, linear progression.
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  • 15
    Gonum

    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. We encourage...
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  • 16
    DeepCTR

    DeepCTR

    Package of deep-learning based CTR models

    DeepCTR is a Easy-to-use,Modular and Extendible package of deep-learning based CTR models along with lots of core components layers which can be used to easily build custom models. You can use any complex model with model.fit(), and model.predict(). Provide tf.keras.Model like interface for quick experiment. Provide tensorflow estimator interface for large scale data and distributed training. It is compatible with both tf 1.x and tf 2.x. With the great success of deep learning,DNN-based...
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  • 17
    DeepCTR-Torch

    DeepCTR-Torch

    Easy-to-use,Modular and Extendible package of deep-learning models

    DeepCTR-Torch is an easy-to-use, Modular and Extendible package of deep-learning-based CTR models along with lots of core components layers that can be used to build your own custom model easily.It is compatible with PyTorch.You can use any complex model with model.fit() and model.predict(). With the great success of deep learning, DNN-based techniques have been widely used in CTR estimation tasks. The data in the CTR estimation task usually includes high sparse,high cardinality categorical...
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  • 18
    Emb-GAM

    Emb-GAM

    An interpretable and efficient predictor using pre-trained models

    ... for each input before learning a linear model in the embedding space. The final model (which we call Emb-GAM) is a transparent, linear function of its input features and feature interactions. Leveraging the language model allows Emb-GAM to learn far fewer linear coefficients, model larger interactions, and generalize well to novel inputs. Across a variety of natural-language-processing datasets, Emb-GAM achieves strong prediction performance without sacrificing interpretability.
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  • 19
    LQSTFM is a Matlab toolbox for handling linear quaternion systems. It requires the QTFM toolbox to provide the underlying quaternion operations.
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  • 20
    Shotcut

    Shotcut

    Shotcut is a free, open source, cross-platform video editor.

    Shotcut is a free, open source, cross-platform video editor for Windows, Mac and Linux. Major features include support for a wide range of formats; no import required meaning native timeline editing; Blackmagic Design support for input and preview monitoring; and resolution support to 4k. Copyright © 2011-2023 by Meltytech, LLC Shotcut is a trademark of Meltytech, LLC.
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    Downloads: 63,256 This Week
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  • 21
    NetTopologySuite

    NetTopologySuite

    A .NET GIS solution that is fast and reliable for the .NET platform.

    A .NET GIS solution that is fast and reliable for the .NET platform. NetTopologySuite is a direct port of all the functionalities offered by JTS Topology Suite: NTS exposes JTS in a '.NET way', for example using Properties, Indexers, etc. The JTS Topology Suite is an API for modeling and manipulating 2-dimensional linear geometry. It provides numerous geometric predicates and functions. JTS conforms to the Simple Features Specification for SQL published by the Open GIS Consortium.
    Downloads: 1 This Week
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  • 22
    DifferenceKit

    DifferenceKit

    A fast and flexible O(n) difference algorithm framework

    A fast and flexible O(n) difference algorithm framework for Swift collection. The algorithm is optimized based on the Paul Heckel’s algorithm. This is a diffing algorithm developed for Carbon, works stand alone. The algorithm optimized based on the Paul Heckel’s algorithm. See also his paper A technique for isolating differences between files released in 1978. It allows all kind of diffs to be calculated in linear time O(n). RxDataSources and IGListKit are also implemented based on his...
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  • 23
    Linfa

    Linfa

    A Rust machine learning framework

    linfa aims to provide a comprehensive toolkit to build Machine Learning applications with Rust. Kin in spirit to Python's scikit-learn, it focuses on common preprocessing tasks and classical ML algorithms for your everyday ML tasks.
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  • 24
    Octave Forge

    Octave Forge

    A collection of packages providing extra functionality for GNU Octave

    Octave Forge is a central location for collaborative development of packages for GNU Octave. The Octave Forge packages expand Octave's core functionality by providing field specific features via Octave's package system. See https://octave.sourceforge.io/packages.php for a list of all available packages. GNU Octave is a high-level interpreted language, primarily intended for numerical computations. It provides capabilities for the numerical solution of linear and nonlinear problems...
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    Downloads: 3,140 This Week
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  • 25
    XFLR5

    XFLR5

    XFLR5 is an analysis tool for airfoils, wings and planes

    XFLR5 includes the xfoil program for foil analysis, and several 3d analysis methods for planes : - a non-linear lifting line method for standalone wings - two vortex-lattice and a 3d panel method for the analysis of aerodynamic performance of wings and plane operating at low Reynolds numbers The latest v6 version introduces stability analysis of planes.
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    Downloads: 2,191 This Week
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