📄 Official implementation regarding the paper "Genetic Programming Operators into Artificial Machine Learning Losses".

Tópicos en Inteligencia Artificial

RULSTM Loss Functions Code, Used to aid in experimentation with architecture testing

Implementation of the Class Distance Weighted Cross-Entropy Loss in PyTorch.

Notes on implementation part of Cross Entropy Loss

Discover the main building blocks of neural networks and understand the three main neural network architectures. Explore the process of solving a regression data problem

[ISBI2020] Kappa loss for skin lesion segmentation in fully convolutional network

Here you will find R Codes and bibliography related to Loss Models Theory.

Machine learning projects using Kaggle datasets

This repo serves as a showcase for the implementation of various cost functions commonly used in the measurement of efficient weights and biases during the critical phase of backward propagation in neural networks.

AI | ML | DL Fully Covered for Basic

AIND Jupyter Notebook to predict student admissions using Keras Neural Networks

A feedforward neural network to predict wine quality based on a number of scientific factors. NOTE: This is purely an educational project. This is neither an efficient nor realistic neural network for commercial use.

Performing gradient descent for calculating slope and intercept of linear regression using sum square residual or mean square error loss function.

A compilation of loss functions for optimization problems

Technological review about the different Learning to Rank approaches: pointwise, pairwise, and listwise

Analysis of Directional Distortion on Stripe Regions in Deep Learning Image Coding Based on MS-SSIM

This repository contains the code for the blog post on Understanding L1 and L2 regularization in machine learning. For further details, please refer to this post.

All loss function and metrics related to segmentation model in one repo.