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Jan 31, 2019 - Python
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Machine-Learning-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.
Calibration of an air pollution sensor monitoring network in uncontrolled environments with multiple machine learning algorithms
Code and Simulations using Bayesian Approximate Kernel Regression (BAKR)
Implementation of various Machine Learning Algorithms and Machine Learning Concepts in Python
Shared Bike Volumn Prediction
Sequential Regression Extrapolation (SRE): An accurate method of extrapolation using machine learning
Nonparametric regression examples with R and Python
A library of smoothing kernels in multiple languages for use in kernel regression and kernel density estimation.
Tool for non-parametric curve fitting using local polynomials.
This R package repository performs optimal transport and kernel regression hypothesis testing. Functions to perform large scale simulations are also provided.
My realization of kernel regression.
Assess Balance with Machine Learning
This repo contains an R package to execute ROKET's real data analysis workflow on TCGA cancer types
Anisotropic smoothing for change-point regression data
My implementation of some algorithms
Guide for the Baccarelli Lab GitHub
Identifying the most influential food groups on COVID-19 recovery rate: exploratory data analysis and statistical modeling
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