GPU-accelerated Levenberg-Marquardt curve fitting in CUDA

High Quality Geophysical Analysis provides a general purpose Bayesian and deterministic inversion framework for various geophysical methods and spatially distributed / timeseries data

Ceres.js is a javascript port of the Ceres solver. Ceres Solver is an open source C++ library for modeling and solving large, complicated optimization problems. It can be used to solve Non-linear Least Squares problems with bounds constraints and general unconstrained optimization problems. It is a mature, feature rich, and performant library.

Training of a neural network for nonlinear regression prediction with TensorFlow and Keras API.

**curve_fit_utils** is a Python module containing useful tools for curve fitting

Symbolic XAI explainable machine learning & non-linear regression platform for MATLAB

C++ wrapper of gsl non-linear least-squares fit.

AI/ML Engineer – Stage 2 provides in-depth knowledge about supervised learning algorithms, also known as supervised machine learning, which is a subcategory of machine learning and artificial intelligence. It is defined by its use of labelled datasets to train algorithms to classify data or predict outcomes accurately.

Define, build, and evaluate machine learning models for real-world applications

The projects are part of the graduate-level course CSE-574 : Introduction to Machine Learning [Spring 2019 @ UB_SUNY] . . . Course Instructor : Mingchen Gao (https://cse.buffalo.edu/~mgao8/)

ANFIS Non-Linear Regression for Average Localization Error Dataset

Machine Learning project. Implementation of different linear and non linear regression and finding out which one is best for us

This is Repository in which I will upload projects done in MTH 686 A in IIT Kanpur . The course instructor is our favorite and respected Sir Debashis Kundu

Shiny interface for growth model fit

A C++ header-only library for useful tools on optimization, statistics and curve fitting

Mixtures-of-ExperTs modEling for cOmplex and non-noRmal dIsTributionS

This repository is intended to provide a slideshow of classification models, with a focus on the statistical properties of each approach. Specifically, a wide variety of both linear and non-linear methods are adopted and then compared, ranging from Linear Probability Model and Logistic Regression to Quadratic Discriminant Analysis and Generalised Additive Models.

Non-linear model fitting of time distribution of biological phenomena

Repo for the famous SA Heart Disease dataset. We demonstrate the importance of considering non-linear terms, and using splines in R.

This project is on Data Mining process using R depending on ISLR book.

This repository is on Machine Learning using Python 3.8.3 using Visual Studio Code. Most of the programs are from IBM Machine Learning course and some algorithms (course out of scope) are presenterd only for learning purpose. These codes will be on topics like Regression, Classification, Clustering and Recommender Systems.

Analysis of Public High Schools Admitting Students by Examination in Turkey

Regression problem predicting Boston house prices in RStudio

Multi term Polynomial Regression with Learnable Exponents and Coefficients (+L1 Regularisation for Term Pruning & Coefficient/Exponent Based Feature augmentation)

Machine Learning (ML) by using Python

Implemented Traditional ML models for Regression and Classification using sklearn.

This library gives a modular design for better control of gradient passing between architecture components. Useful for architectures not using a traditional forward and backward pass.

No description provided.

Graduation Final Project on electrical engineering (PUC-Rio)

No description provided.