Topic: kernel-ridge-regression Goto Github
Some thing interesting about kernel-ridge-regression
Some thing interesting about kernel-ridge-regression
kernel-ridge-regression,Machine Learning Code Implementations in Python
User: amishasomaiya
kernel-ridge-regression,
User: antoniasavu
kernel-ridge-regression,Assignments
User: anupriya1519
kernel-ridge-regression,MLQD is a Python Package for Machine Learning-based Quantum Dissipative Dynamics
User: arif-phychem
kernel-ridge-regression,Speeding up quantum dissipative dynamics of open systems with kernel methods
User: arif-phychem
kernel-ridge-regression,Kernel-Methods on a Red-Wine Dataset
User: benjaminrueling
kernel-ridge-regression,Amons-based quantum machine learning for quantum chemistry
User: binghuang2018
kernel-ridge-regression,Sequential Regression Extrapolation (SRE): An accurate method of extrapolation using machine learning
User: butler-julie
Home Page: https://butler-julie.github.io/SRE/
kernel-ridge-regression,This repository contains code for predicting stock prices using various machine learning models. The models implemented include Linear Regression, SVM Regression, KNN Regression, Kernel Ridge Regression, and Ridge Regression.
User: danielchristopher513
kernel-ridge-regression,AI-enhanced computational chemistry
User: dralgroup
Home Page: http://mlatom.com
kernel-ridge-regression,Explore selected topics related to Gaussian processes
User: elcorto
Home Page: https://elcorto.github.io/gp_playground
kernel-ridge-regression,pwtools is a Python package for pre- and postprocessing of atomistic calculations, mostly targeted to Quantum Espresso, CPMD, CP2K and LAMMPS. It is almost, but not quite, entirely unlike ASE, with some tools extending numpy/scipy. It has a set of powerful parsers and data types for storing calculation data.
User: elcorto
Home Page: https://elcorto.github.io/pwtools
kernel-ridge-regression,Machine learning regression model to predict energy consumption and GHG emission
User: ericpaul075
kernel-ridge-regression,Pytorch implementation of Alchemical Kernels from Phys. Chem. Chem. Phys., 2018,20, 29661-29668
User: jakublala
kernel-ridge-regression,Scripts for machine learning at ONR project (2017-)
User: jyuan1986
kernel-ridge-regression,Self-Distillation with weighted ground-truth targets; ResNet and Kernel Ridge Regression
User: kennethborup
kernel-ridge-regression,Cross-validation, knn classif, knn régression, svm à noyau, Ridge à noyau
User: lanmar
kernel-ridge-regression,Neo LS-SVM is a modern Least-Squares Support Vector Machine implementation
User: lsorber
kernel-ridge-regression,This repository contains the source code of my bachelors' thesis.
User: luansousac
kernel-ridge-regression,Implementation of (Kernel) Ridge Regression predictors from scratch on Kaggle's Spotify Tracks Dataset.
User: lukebella
kernel-ridge-regression,PERK: Parameter Estimation via Regression with Kernels
Organization: magneticresonanceimaging
kernel-ridge-regression,Codes and images used for blog article at https://www.mdelcueto.com/blog/kernel-ridge-regression-tutorial/
User: marcosdelcueto
kernel-ridge-regression,Anticipate the energy consumption of new commercial buildings
User: mrcreasey
kernel-ridge-regression,SM4ML project
User: nemolino
kernel-ridge-regression,2017 Summer School on the Machine Learning in the Molecular Sciences. This project aims to help you understand some basic machine learning models including neural network optimization plan, random forest, parameter learning, incremental learning paradigm, clustering and decision tree, etc. based on kernel regression and dimensionality reduction, feature selection and clustering technology.
User: nickcafferry
Home Page: https://nickcafferry.github.io/Machine-Learning-in-the-Molecular-Sciences/
kernel-ridge-regression,2018 [Julia v1.0] machine learning (linear regression & kernel-ridge regression) examples on the Boston housing dataset
User: qin-yu
kernel-ridge-regression,House Prices - Advanced Regression Techniques
User: saharnasiri
kernel-ridge-regression,Contains ML Algorithms implemented as part of CSE 512 - Machine Learning class taken by Fransico Orabona. Implemented Linear Regression using polynomial basis functions, Perceptron, Ridge Regression, SVM Primal, Kernel Ridge Regression, Kernel SVM, Kmeans.
User: sudeshnapal12
kernel-ridge-regression,Codes and experiments for paper "Distributed Learning with Random Features". Preprint.
User: superlj666
kernel-ridge-regression,Lecture "Learning & soft computing" @FH-Wedel SS22
User: tjarkpr
kernel-ridge-regression,Lecture "Softwareprojekt" @FH-Wedel WS20
User: tjarkpr
kernel-ridge-regression,kernel linear regression and svm for Creditcard and Tumor data
User: windhaunting
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