The set of CPU/GPU optimised regularisation modules for iterative image reconstruction and other image processing tasks

TOmographic MOdel-BAsed Reconstruction (ToMoBAR) software

My project to recreate the results in "Understanding Deep Learning Requires Rethinking Generalization"

The use case is an application of the regularization technique such as Ridge and Lasso for building a linear regression model for housing price prediction.

Python code to fit single-angle dynamic light scattering data using the Tikhonov Philips regularisation

Various regularized regression models for predicting car prices, using web scraped data

Multivariate Polynomial Regression using gradient descent with regularisation

In the context of Deep Learning: What is the right way to conduct example weighting? How do you understand loss functions and so-called theorems on them?

Horseshoe regression model fitted in PyMC.

Repo for machine learning classes

A series of Online Courses Offered by deeplearning.ai on Coursera.

Regularisation and Cross-Validation of Determinants of Egalitarian Democracy: Demonstration for R

Content: Classification, Sigmoid function, Decision Boundary, Cost function, Gradient descent, Overfitting, Regularisation

a small machine learning theory practice.

The goal of this project is to develop and test two text classification systems: Task 1: sentiment analysis, in particular to predict the sentiment of movie review, i.e. positive or negative (binary classification). Task 2: topic classification, to predict whether a news article is about International issues, Sports or Business (multiclass class…

In this project, we use differents methods to transform our dataset (usually dimension modification) before making prediction thanks to machine learning and regressions.

In this project we will build multiple CNN models for CIFAR-10 Image Classification

The purpose of this study is to visualise and see how changing the regularisation constant affects svm classification. SVM with linear kernel has been used.

GEARS a toolbox for Global parameter Estimation with Automated Regularisation via Sampling by Jake Alan Pitt and Julio R. Banga