Search Results for "learning"
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Showing 35 open source projects for "learning"
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Application Monitoring That Won't Slow Your App DownFull APM with errors, performance, logs, and uptime monitoring. 99.999% uptime SLA on the platform itself.
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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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MATLAB Deep Learning Model Hub
Discover pretrained models for deep learning in MATLAB
Discover pre-trained models for deep learning in MATLAB. Pretrained image classification networks have already learned to extract powerful and informative features from natural images. Use them as a starting point to learn a new task using transfer learning. Inputs are RGB images, the output is the predicted label and score. -
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FEATool Multiphysics
Physics Simulation Made Easy" (Fully Integrated FEA, FEniCS
...By providing a truly easy to use and integrated all-in-one simulation platform for multi-physics analysis, makes FEATool an ideal simulation and modeling tool for everyone from students learning mathematical modeling, to researchers and engineers wishing to explore new ideas in a no fuss, simple, and convenient way. -
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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: http://arma.sourceforge.net/download.html * Documentation: http://arma.sourceforge.net/docs.html * Bug reports: http://arma.sourceforge.net/faq.html * Git repo: https://gitlab.com/conradsnicta/armadillo-code -
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Eventer
Rapid, unbiased, reproducible analysis of synaptic events
...The software combines deconvolution for detection, and variable length template matching approaches for screening out false positive events. Eventer also includes a machine learning-based approach allowing users to train a model to implement their ‘expert’ selection criteria across data sets without bias. Sharing models allows users to implement consistent analysis procedures. The software is coded in MATLAB, but has been compiled as standalone applications for Windows, Mac and Linux. Please visit the official Eventer website for more info https://eventerneuro.netlify.app/ While the paper is in preparation, please cite as; Winchester, G., Liu, S., Steele, O.G., Aziz, W. and Penn, A.C. (2020) Eventer. ... -
Full-stack observability with actually useful AI | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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FEATool Multiphysics - FEA & CFD Toolbox
FEATool Multiphysics is an easy-to-use FEA and CFD Simulation Toolbox
...In addition to built-in CAD and pre/post-processing, automatic mesh generation, and multi-physics solvers, FEATool also seamlessly integrates the state-of-the-art OpenFOAM [1], SU2, and FEniCS CFD and FEA solvers. Moreover, native itegration with MATLAB and Python allows advanced simulation scripts and programmatic use cases such as in AI and machine learning [2]. [1]: https://www.featool.com/Easy-to-Use-OpenFOAM-GUI/ [2]: https://featool.com/model-showcase/2024-11-12-CFD-and-Flow-Prediction-Based-on-Deep-Learning... -
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mTRF-Toolbox
A MATLAB package for modelling multivariate stimulus-response data
mTRF-Toolbox is a MATLAB package for modelling multivariate stimulus-response data, suitable for neurophysiological data such as MEG, EEG, sEEG, ECoG and EMG. It can be used to model the functional relationship between neuronal populations and dynamic sensory inputs such as natural scenes and sounds, or build neural decoders for reconstructing stimulus features and developing real-time applications such as brain-computer interfaces (BCIs). Toolbox Paper: ... -
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STK
a Small (Matlab/Octave) Toolbox for Kriging
...Even though it is, currently, mostly geared towards the Design and Analysis of Computer Experiments (DACE), the STK can be useful for other applications areas (such as Geostatistics, Machine Learning, Non-parametric Regression, etc.). -
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Mathematics
Accumulation of mathematical knowledge, matrix numerical optimization
...The goal is to provide learners, researchers, and developers with a consolidated source of foundational and advanced mathematical concepts. By gathering a diverse set of topics into one repository, it supports continuous learning and interdisciplinary exploration. Its open source nature allows for community contributions and adaptation to different educational or research needs. -
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The main goal of this project is to develop new algorithms of machine learning and collect examples of existing methods. This collection pursues scientific and educational purposes.
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Try Google Cloud Risk-Free With $300 in CreditUse your credit across every product. Compute, storage, AI, analytics. When it runs out, 20+ products stay free. You only pay when you choose to.
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SAR Synthetic Aperture Radar
Collection of MATLAB codes, simulations, and summaries
...Range-Doppler (RD) algorithm, Chirp Scaling (CS) algorithm), synthetic scenes, InSAR (interferometric) simulation including multiple terrain types (flat, conical), and polarization calibration techniques (Whitt, PARC, Quegan, Ainsworth). The readme states that these were research/learning codes, with experiments and reports, and no further maintenance is expected. InSAR (interferometric SAR) simulation and processing. PolSAR (polarimetric SAR) calibration algorithms. -
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An alignment-free standalone tool with interactive graphical user interface for DNA sequence comparison and analysis
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Phenalysis
Analyze agronomic plant research plots in aerial orthomosaic images.
A graphical user interface to import, analyze and export plots from orthomosaic images of agronomic trials. Please cite the following reference in your work if you use Phenalysis: Khan Z and Miklavcic SJ (2019) An Automatic Field Plot Extraction Method From Aerial Orthomosaic Images. Front. Plant Sci. 10:683. doi: https://doi.org/10.3389/fpls.2019.00683 This tool is being developed through the sponsorship of the Australian Research Council's Industrial Transformation Research Hub on... -
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MATLAB Robotics
MATLAB sample codes for mobile robot navigation
...It provides practical algorithmic implementations such as A*, RRT, Kalman filters, particle filters, and SLAM, making it a valuable resource for students, researchers, and developers learning or prototyping robotics applications. The code is written to be accessible and easy to adapt, enabling experimentation with both classical and modern robotics techniques. By using MATLAB’s visualization and numerical capabilities, the repository offers intuitive demonstrations of algorithms in action. As an open resource, it encourages contributions and serves as a foundation for building and testing robotics concepts in simulation. -
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All future developments will be implemented in the new MATLAB toolbox SciXMiner, please visit https://sourceforge.net/projects/scixminer/ to download the newest version. The former Matlab toolbox Gait-CAD was designed for the visualization and analysis of time series and features with a special focus to data mining problems including classification, regression, and clustering.
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Density-ratio based clustering
Discovering clusters with varying densities
This site provides the source code of two approaches for density-ratio based clustering, used for discovering clusters with varying densities. One approach is to modify a density-based clustering algorithm to do density-ratio based clustering by using its density estimator to compute density-ratio. The other approach involves rescaling the given dataset only. An existing density-based clustering algorithm, which is applied to the rescaled dataset, can find all clusters with varying... -
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Mass-based dissimilarity
A data dependent dissimilarity measure based on mass estimation.
This software calculates the mass-based dissimilarity matrix for data mining algorithms relying on a distance measure. References: Overcoming Key Weaknesses of Distance-based Neighbourhood Methods using a Data Dependent Dissimilarity Measure. KDD 2016 http://dx.doi.org/10.1145/2939672.2939779 The source code, presentation slide and poster are attached under "Files". The presentation video in KDD 2016 is published on https://youtu.be/eotD_-SuEoo . Since this software is licensed... -
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Face Recognition System
Face Recognition System Matlab source code
Research on automatic face recognition in images has rapidly developed into several inter-related lines, and this research has both lead to and been driven by a disparate and expanding set of commercial applications. The large number of research activities is evident in the growing number of scientific communications published on subjects related to face processing and recognition. Index Terms: face, recognition, eigenfaces, eigenvalues, eigenvectors, Karhunen-Loeve algorithm. -
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Fingerprint Recognition System
Fingerprint Recognition System 5.3 - Matlab source code
The proposed filter-based algorithm uses a bank of Gabor filters to capture both local and global details in a fingerprint as a compact fixed length FingerCode. The fingerprint matching is based on the Euclidean distance between the two corresponding FingerCodes and hence is extremely fast. We are able to achieve a verification accuracy which is only marginally inferior to the best results of minutiae-based algorithms published in the open literature. Our system performs better than a... -
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LWPR
Locally Weighted Projection Regression (LWPR)
...A locally weighted variant of Partial Least Squares (PLS) is employed for doing the dimensionality reduction. Please cite: [1] Sethu Vijayakumar, Aaron D'Souza and Stefan Schaal, Incremental Online Learning in High Dimensions, Neural Computation, vol. 17, no. 12, pp. 2602-2634 (2005). [2] Stefan Klanke, Sethu Vijayakumar and Stefan Schaal, A Library for Locally Weighted Projection Regression, Journal of Machine Learning Research (JMLR), vol. 9, pp. 623--626 (2008). More details and usage guidelines on the code website. -
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Matlab Community Detection Toolbox
CDTB is a MATLAB toolbox which performs Community Detection
We present the Community Detection Toolbox (CDTB), a MATLAB toolbox which can be used to perform community detection. The CDTB contains several functions from the following categories. 1. graph generators; 2. clustering algorithms; 2. cluster number selection functions; 4. clustering evaluation functions. Furthermore, CDTB is designed in a parametric manner so that the user can add his own functions and extensions. The CDTB can be used in at least three ways. The user can employ... -
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MIT SPHERES Simulation (Release)
MIT's spacecraft simulator for control algorithm development
...The simulation code base consists of simulated versions of most of the SPHERES core flight code and additional code that simulates dynamics, communications, and other environmental interaction. The simulation is particularly valuable during the early stages of algorithm development and implementation as an aid in accelerating the learning curve for any Guest Scientist for SPHERES. Algorithms may be implemented in C or Embedded MATLAB and executed in the MATLAB simulation environment to verify general desired behavior. With some limitations, the code used in the simulation can be directly transferred to the SPHERES hardware. We are sharing this project with the public to gather more interest for SPHERES Guest Scientists. ... -
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MCTIMME
Microbial Counts Trajectories Infinite Mixture Model Engine
MCTIMME is a nonparametric Bayesian computational framework for analyzing microbial time-series data.The current implementation is in Matlab. -
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lonestar
A feature selection and classification algorithm based on L1 Norm SVM
A feature selection and classification algorithm. It is based on L1 Norm Support Vector Machine with t-test and Recursive Feature Elimination. -
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