model-fitting
There are 0 repository under model-fitting topic.
- Language:C++ 985
pytorchbearer / torchbearer
torchbearer: A model fitting library for PyTorch
Language:Python 633zfit / zfit
Model manipulation and fitting library based on TensorFlow and optimised for simple and direct manipulation of probability density functions. Its main focus is on scalability, parallelisation and user friendly experience.
Language:Python 168chasmani / piecewise-regression
piecewise-regression (aka segmented regression) in python. For fitting straight line models to data with one or more breakpoints where the gradient changes.
Language:Python 84astrorama / SourceXtractorPlusPlus
SourceXtractor++, the next generation SExtractor
Language:C++ 66- jetset
andreatramacere / jetset
JetSeT a framework for self-consistent modeling and fitting of astrophysical relativistic jets
Language:Python 27 NeuralEnsemble / neurotune
Package for fitting/optimization of NeuroML models
Language:Python 16quantumjot / PyFolding
Python framework for multi-parameter optimization and evaluation of protein folding models
Language:Python 16VipulRamtekkar / Active-Appearance-Models
Course Project for the course CS 736
Language:Python 16tatha04 / Housing-Prices-Advanced-Regression-Techniques
This notebook explores the housing dataset from Kaggle to predict Sales Prices of housing using advanced regression techniques such as feature engineering and gradient boosting.
Language:Jupyter Notebook 15NMikolajewicz / MetaLab
Meta-analysis toolbox for basic research applications. Developed in MATLAB R2016b.
Language:MATLAB 9adbecker / tsiR
tsiR: An R package for time-series Susceptible-Infected-Recovered models of epidemics
Language:R 7anilbey / Nonlinear-Model-Identification-with-FROE
Implementation of the algorithm described in the following paper. Korenberg, M., Billings, S.A. and Liu, Y.P. (1987) An Orthogonal Parameter Estimation Algorithm for Nonlinear Stochastic Systems
Language:MATLAB 5int-brain-lab / ibl-changepoint
Toolbox for change-point detection and ideal-observer analyses of IBL task data
Language:Jupyter Notebook 5poissonconsulting / universals
An R package of S3 generic methods for Bayesian analyses that generate MCMC samples
Language:R 4alexandershaw4 / aoptim
a gradient-based optimisation routine for highly parameterised non-linear dynamical models
Language:MATLAB 3omyllymaki / ransac-solver
General RANSAC solver with detailed examples.
Language:Python 3- Language:R 2
JaPitt / GEARS
GEARS a toolbox for Global parameter Estimation with Automated Regularisation via Sampling by Jake Alan Pitt and Julio R. Banga
Language:MATLAB 2lacerbi / nyu2023-bayes
Tutorial on Bayesian model fitting with (Py)VBMC.
Language:Jupyter Notebook 2- Language:MATLAB 2
AlessandroMessori / Preference-Selection-Automatic-Cut
Automatic Dendrogram Cut integration for preference based Computer Vision Model Fitting algorithms
Language:Python 1Briankim254 / mushroom-classifier
This repository hosts a machine learning-based mushroom identification system, utilizing scikit-learn models in a Jupyter notebook. The project analyzes and processes a Kaggle dataset to train a model that classifies mushrooms as edible or poisonous, providing a reliable tool for mushroom enthusiasts and foragers.
Language:Jupyter Notebook 1devosmitachatterjee2018 / Computer_Vision
The project involves projective geometry, geometric transformations, modelling of cameras, feature extraction, stereo vision, recognition and deep learning, 3d-modelling, geometry of surfaces and their silhouettes, tracking, and visualisation.
Language:MATLAB 1dteuscher1 / NBA-Basketball-Visualization
Visualization and model fitting for Kobe Bryant shots over the course of his career. Data comes from the Kobe Bryant Shot Selection Kaggle Competition
Language:HTML 1miguelangelnieto / Finding-Donors-for-CharityML
Investigated factors that affect the likelihood of charity donations being made based on real census data. Developed a naive classifier to compare testing results to. Trained and tested several supervised machine learning models on preprocessed census data to predict the likelihood of donations. Selected the best model based on accuracy, a modified F-scoring metric, and algorithm efficiency.
Language:HTML 1Olrez / HVAC_model_regression
HVAC model fitting tool from measured data, basic tkinter gui
Language:Python 1priyalfatewar / Data-Analytics-Project-on-Gender-Classification
Data Analytics on a simple gender classification dataset taken from kaggle. Univariate bivariate and multivariate analysis EDA and model fitting
Language:Jupyter Notebook 1shridhar1504 / Foreign-Exchange-Rate-Time-series-Datascience-Project
This project will use time series analysis to forecast the exchange rate between the euro and the US dollar. The project will use a variety of statistical techniques, such as ARIMA to model the data and forecast the exchange rate.
Language:Jupyter Notebook 1Siddharth1989 / WranglingRealEstateData
Wrangled real estate data from multiple sources and file formats, brought it into a single consistent form and analysed the results.
Language:Jupyter Notebook 1Balajimohan18 / Foreign-Exchange-Rate-Time-Series-Datascience-Project
This project will use time series analysis to forecast the exchange rate between the euro and the US dollar. The project will use a variety of statistical techniques, such as ARIMA to model the data and forecast the exchange rate.
Language:Jupyter Notebook 0- smart-cfa
phdpablo / smart-cfa
Solution in the form of a tutorial article wherein the key decisions made in conducting a CFA are validated through recent literature and presented within a dynamic document framework.
Language:TeX 0 aleniart / multiple_linear_regression_customers
Multiple linear regression model based on eCommerce customers data in Python language.
Language:Jupyter Notebookarnestc / StatisticalLearning
Labs for the "Statistical Learning and Neural Networks" course @ Polytechnic University of Turin
Language:Jupyter Notebookneurorishika / pyGORL
Python-based fitting of 1-state MDP Reinforcement Learning algorithms using Global Optimization (Turner Lab, HHMI, 2023)
Language:HTMLDevelop a data science project using historical sales data to build a regression model that accurately predicts future sales. Preprocess the dataset, conduct exploratory analysis, select relevant features, and employ regression algorithms for model development. Evaluate model performance, optimize hyperparameters, and provide actionable insights.
Language:Jupyter Notebook
