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adversarialnetspapers

The classical papers and codes about generative adversarial nets

all_files

auto-sklearn

Automated Machine Learning with scikit-learn

bayesclass

Bayesian Estimators

bayesnet

Some Bayesian Classifiers using Torchlib

beflask

Web app to manage the benchmark results

codes

Codes for some of my co-authored journal/conference papers

combatharmonization

Harmonization of multi-site imaging data with ComBat

correlation-based-feature-selection

Implementation and test of CFS

data-science-learning

Repository of code and resources related to different data science and machine learning topics. For learning, practice and teaching purposes.

datasets

Machine learning datasets used in tutorials on MachineLearningMastery.com

deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

diffusionbee-stable-diffusion-ui

Diffusion Bee is the easiest way to run Stable Diffusion locally on your M1 Mac. Comes with a one-click installer. No dependencies or technical knowledge needed.

discretization-mdlpc

Discretization with Fayyad and Irani's minimum description length principle criterion (MDLPC)

entropy_estimators

Estimators for the entropy and other information theoretic quantities of continuous distributions

escc_ml

Deep-learning Radiomics for Classification Modelling

fcbf

Houses implementation of the Fast Correlation-Based Filter (FCBF) feature selection method.

fimdlp

Fayyad - Irani MDLP discretization algorithm

ilearndeeplearning.py

This repository contains small projects related to Neural Networks and Deep Learning in general. Subject are closely linekd with articles I publish on Medium. I encourage you both to read as well as to check how the code works in the action.

imagen-pytorch

Implementation of Imagen, Google's Text-to-Image Neural Network, in Pytorch

mdlp

An implementation of the minimum description length principal expert binning algorithm by Usama Fayyad

mi-nee

Mutual Information Neural Entropic Estimation

ml-stanford

Ejercicios de programación del curso Machine Learning de Stanford en Coursera

mlalgorithms

Minimal and clean examples of machine learning algorithms implementations

mufs

Implementation of Fast Correlation-Based Filter and Correlation-based Feature Selection

murthy-oc1

The source for the paper "A System for Induction of Oblique Decision Trees" by S. K. Murthy and code for the original OC1.

neuralnetwork

Neural Network implementation based on the Andrew Ng courses

npeet

Non-parametric Entropy Estimation Toolbox

npeet_lnc

local non-uniformity correction for mutual information estimation

odte

Oblique Decision Tree Ensemble