doing audio digital signal processing in tensorflow to try to recreate digital audio effects
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Updated
Dec 6, 2022 - Python
doing audio digital signal processing in tensorflow to try to recreate digital audio effects
MITx 6.86x | Machine Learning with Python | From Linear Models to Deep Learning
Fitting dose-response models in R
Nonlinear regression in Julia
Python implementation of Levenberg-Marquardt algorithm built from scratch using NumPy.
one day introduction to generalized nonlinear models using the gnm and logmult R packages
GPU/TPU accelerated nonlinear least-squares curve fitting using JAX
GMPE-estimation implements a one-stage estimation algorithm to estimate ground-motion prediction equations (GMPE) with spatial correlation. It also quantifies the uncertainty of spatial correlation and intensity measure predictions.
Robust Gaussian Process with Iterative Trimming
Assignments for the Machine Learning bachelor course @USI22/23
Neural nets for high accuracy multivariable nonlinear regression.
Robust Regression for arbitrary non-linear functions
Code and Simulations using Bayesian Approximate Kernel Regression (BAKR)
Easy to use high level python library for popular machine learning algorithms. Has in-built support for graphing and optimizers based in C++.
Nonlinear Regression based on scikit-learn.
Benchmark a given function for variable input sizes and find out its time complexity
a c++ library with statistical machine learning algorithms for linear and non-linear robust regression that can be used with python.
Nonlinear Regression for Agricultural Applications
{gslnls}: GSL multi-start nonlinear least-squares fitting in R
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