R

regression

Library for stochastic control

Simple ML Project using regression models and KMeans clustering to predict Y from A and B, classify results, and expose predictions through a FastAPI API.

A framework to train, validate and test regression models

The efficient alternative to Neural Networks. Implements SLRM (Segmented Linear Regression Model) for neural compression and non-linear data modeling, achieving high precision with a fraction of the parameters of a traditional ANN.

A bot to help with Linux kernel regression tracking: https://linux-regtracking.leemhuis.info/about/

A TensorFlow/Keras neural network for regression on noisy sine wave data, predicting continuous values with real-time visualization of predictions and loss using Matplotlib.

Comment prédire le prix de vente d'une maison en fonction de ses caractéristiques ?

House Prices Competition on Kaggle

Probability and Statistics A regression model for predicting how patients will rate their pain in 12 months.

Endgoal: a comparison of categorisation algorithms and techniques for a specific task (regression models for auction bidding data to determine bid categories) Most of the work: data preprocessing and aggregation

Projet de prédiction de la taille des poissons du marché de par régression. Article technique disponible sur mon blog : https://boulayc.gitlab.io/blog/

An example of tabular data regression (parameter estimates) using TabNet

My attempts to solve homework from the Moscow Institute of Physics and Technology course

Collection of completed data-mining (university course) on python

Performing weighted orthogonal regression

Analisi di un dataset contenenti informazioni su diverse tipologie di vetro.

But the plans were on display …

"Cloud container data analytics, statistical modeling, and machine learning on distributed databases". "A free opensource alternative to SPSS, SAS, MATLAB, PowerBI, Tableau and Alteryx". Runs on Linux, Windows, MacOS, and in the cloud via containers.

Code for the undergrad thesis "'Bootstrap methods for GLM, GAM and GPLM"

Machine Learning - Regression Problem