Search Results for "fitting"
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Showing 241 open source projects for "fitting"
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eos
A lightweight 3D Morphable Face Model library in modern C++
eos is a lightweight 3D Morphable Face Model fitting library that provides basic functionality to use face models, as well as camera and shape fitting functionality. It's written in modern C++11/14. MorphableModel and PcaModel classes to represent 3DMMs, with basic operations like draw_sample(). Supports the Surrey Face Model (SFM), 4D Face Model (4DFM), Basel Face Model (BFM) 2009 and 2017, and the Liverpool-York Head Model (LYHM) out-of-the-box. -
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Polynomials.jl
Polynomial manipulations in Julia
Basic arithmetic, integration, differentiation, evaluation, root finding, and fitting for univariate polynomials in Julia. -
3
GLM.jl
Generalized linear models in Julia
...@formula) and matrix-based interfaces, allowing both high-level convenience and low-level control. Under the hood, GLM.jl separates the linear predictor and response objects, allowing flexible combinations of link functions, variance structures, and fitting methods. -
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Toloka-Kit
Toloka-Kit is a Python library for working with Toloka API
...For example, you can pass data between two related projects: one for data labeling, and another for its validation. AutoQuality feature which automatically finds the best fitting quality control rules for your project. -
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BasicBSpline.jl
Basic (mathematical) operations for B-spline functions
Basic (mathematical) operations for B-spline functions and related things with Julia. -
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Lasso.jl
Lasso/Elastic Net linear and generalized linear models
Lasso.jl is a pure Julia implementation of the glmnet coordinate descent algorithm for fitting linear and generalized linear Lasso and Elastic Net models. -
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hctsa
Highly comparative time-series analysis
hctsa is a Matlab software package for running highly comparative time-series analysis. It extracts thousands of time-series features from a collection of univariate time series and includes a range of tools for visualizing and analyzing the resulting time-series feature matrix. -
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Mixed-effects models in Julia
A Julia package for fitting (statistical) mixed-effects models
This package defines linear mixed models (LinearMixedModel) and generalized linear mixed models (GeneralizedLinearMixedModel). Users can use the abstraction for statistical model API to build, fit (fit/fit!), and query the fitted models. A mixed-effects model is a statistical model for a response variable as a function of one or more covariates. For a categorical covariate the coefficients associated with the levels of the covariate are sometimes called effects, as in "the effect of using... -
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ROOT
Analyzing, storing and visualizing big data, scientifically
...ROOT provides a very efficient storage system for data models, that demonstrated to scale at the Large Hadron Collider experiments: Exabytes of scientific data are written in columnar ROOT format. ROOT comes with histogramming capabilities in an arbitrary number of dimensions, curve fitting, statistical modeling, and minimization, to allow the easy setup of a data analysis system that can query and process the data interactively or in batch mode, as well as a general parallel processing framework, RDataFrame, that can considerably speed up an analysis. -
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10
Implicit
Fast Python collaborative filtering for implicit feedback datasets
...All models have multi-threaded training routines, using Cython and OpenMP to fit the models in parallel among all available CPU cores. In addition, the ALS and BPR models both have custom CUDA kernels - enabling fitting on compatible GPU’s. This library also supports using approximate nearest neighbour libraries such as Annoy, NMSLIB and Faiss for speeding up making recommendations. -
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MNE-Python
Magnetoencephalography (MEG) and Electroencephalography EEG in Python
Open-source Python package for exploring, visualizing, and analyzing human neurophysiological data. MNE-Python is an open-source Python package for exploring, visualizing, and analyzing human neurophysiological data such as MEG, EEG, sEEG, ECoG, and more. It includes modules for data input/output, preprocessing, visualization, source estimation, time-frequency analysis, connectivity analysis, machine learning, statistics, and more. -
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GT New Horizons Mod Pack
New Modpack with Gregtech, Thaumcraft and Witchery
...The main intentions of the pack are a long-lasting experience and tying mods together in a progressive fashion, making it feel more like a single game than a compilation of mods thrown together. To reach this goal, GT New Horizons is using the tiers (basically ages of technology) from GregTech and allocates the content of other mods to a fitting point within the progression. Starting in the Stone Age you will barely be able to survive until you get your first steam machines and, eventually, reach electricity. -
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LuxTTS
A high-quality rapid TTS voice cloning model
...Intended for developers, hobbyists, and creators, the repository includes installation instructions, usage examples, and Python APIs that make it feasible to integrate the model in local workflows, web demos, or production systems. Its design emphasizes efficiency and practicality, fitting within modest GPU memory footprints. -
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forecast
Forecasting Functions for Time Series and Linear Models
The forecast package is a comprehensive R package for time series analysis and forecasting. It provides functions for building, assessing, and using univariate forecasting models (e.g. ARIMA, exponential smoothing, etc.), tools for automatic model selection, diagnostics, plotting, forecasting future values, etc. It's widely used in statistics, economics, business forecasting, environmental science, etc. Exponential smoothing state space models (ETS) including seasonal components. Residual... -
15
PySINDy
A package for the sparse identification of nonlinear dynamical systems
...The framework focuses on identifying governing equations that describe the behavior of complex physical systems by selecting sparse combinations of candidate functions. Instead of fitting a purely predictive machine learning model, PySINDy attempts to recover interpretable differential equations that explain how a system evolves over time. This approach is particularly valuable in scientific fields such as physics, engineering, and biology where researchers seek both predictive accuracy and theoretical insight. The library provides tools for constructing libraries of candidate functions, performing sparse regression, and validating discovered models against observed data. ... -
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Spark NLP
State of the Art Natural Language Processing
...Spark ML provides a set of machine learning applications that can be built using two main components, estimators and transformers. The estimators have a method that secures and trains a piece of data to such an application. The transformer is generally the result of a fitting process and applies changes to the target dataset. These components have been embedded to be applicable to Spark NLP. Pipelines are a mechanism for combining multiple estimators and transformers in a single workflow. They allow multiple chained transformations along a machine-learning task. -
17
Kubescape
Kubescape is an open-source Kubernetes security platform for your IDE
An open-source Kubernetes security platform for your clusters, CI/CD pipelines, and IDE that seperates out the security signal from the scanner noise. Kubescape is an open-source Kubernetes security platform, built for use in your day-to-day workflow, by fitting into your clusters, CI/CD pipelines and IDE. It serves as a one-stop-shop for Kubernetes security and includes vulnerability and misconfiguration scanning. You can run scans via the CLI, or add the Kubescape Helm chart, which gives an in-depth view of what is going on in the cluster. Kubescape includes misconfiguration and vulnerability scanning as well as risk analysis and security compliance indicators. ... -
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GMT.jl
Generic Mapping Tools Library Wrapper for Julia
The Generic Mapping Tools, GMT, is an open source collection of tools for manipulating geographic and Cartesian data sets (including filtering, trend fitting, gridding, projecting, etc.) and producing PostScript illustrations ranging from simple x–y plots via contour maps to artificially illuminated surfaces and 3D perspective views. This link will take you to an impressive collection of figures made with GMT. The GMT Julia wrapper was designed to work in a way the close as possible to the command line version and yet to provide all the facilities of the Julia language. ... -
19
Junie
An AI coding agent by JetBrains that ships code from your terminal
...Developers can use Junie through multiple release channels, including stable, EAP, nightly, and experimental builds. Its focus on practical coding automation makes it a useful assistant for speeding up software development while fitting into existing tools and workflows. -
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Kilo
A text editor in less than 1000 LOC with syntax highlight and search
Kilo is a minimalistic terminal text editor written in C, famous for fitting its full implementation into fewer than 1,000 lines of code in a single source file. It was created by Salvatore Sanfilippo (antirez, also known for Redis) as an exercise in writing a small, self-contained editor that others can study and extend. Despite its tiny size, Kilo supports core editor features like opening and saving files, incremental search, and basic syntax highlighting. -
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Self Host Blocks
Modular server management based on NixOS modules
SHB's (Self Host Blocks) is yet another server management tool whose goal is to provide better building blocks for self-hosting. Indeed, SHB provides opinionated building blocks fitting together to self-host any service you'd want. Some common services are provided out of the box. SHB's goal is to make these building blocks plug-and-play. To achieve this, SHB pioneers contracts that allow you, the final user, to be more in control of which pieces go where. The promise here is to let you choose, for example, any reverse proxy you want or any database you want, without requiring work from maintainers of the services you want to self-host. ... -
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PyMC3
Probabilistic programming in Python
PyMC3 allows you to write down models using an intuitive syntax to describe a data generating process. Fit your model using gradient-based MCMC algorithms like NUTS, using ADVI for fast approximate inference — including minibatch-ADVI for scaling to large datasets, or using Gaussian processes to build Bayesian nonparametric models. PyMC3 includes a comprehensive set of pre-defined statistical distributions that can be used as model building blocks. Sometimes an unknown parameter or variable... -
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Extism
The Universal Plug-in System. Extend anything with WebAssembly
Extism is a plug-in system for everyone. We've carefully designed it to be flexible, fitting into codebases of all shapes and sizes, but opinionated enough so that things Just Work™ the way they should. Extism's goal is to make all software programmable. You can use Extism in your codebase, regardless of the programming language. We support several environments through our official Host SDKs, and are adding more language support all the time. -
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brms
brms R package for Bayesian generalized multivariate models using Stan
brms is an R package by Paul Bürkner which provides a high-level interface for fitting Bayesian multilevel (i.e. mixed effects) models, generalized linear / non-linear / multivariate models using Stan as the backend. It allows R users to specify complex Bayesian models using formula syntax similar to lme4 but with far more flexibility (distributions, link functions, hierarchical structure, nonlinear terms, etc.). -
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clj-http
An idiomatic clojure http client wrapping the apache client
clj-http is a popular Clojure library for making HTTP requests, built as a wrapper around Apache’s HttpClient. It uses Ring-style request/response maps and middleware, fitting seamlessly into idiomatic Clojure applications. clj-http allows coercing the body of the request either before it is sent (input coercion), or after it’s received (output coercion) from the server. By default, JSON coercion is only applied when the response’s status is considered “unexceptional”. If the :unexceptional-status option is provided, then its value is a function that specifies what status codes are unexceptional. ...
