loss functions

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Machine Learning Glossary

Loss Functions Cross-Entropy Hinge Huber Kullback-Leibler RMSE MAE (L1) MSE (L2) Cross-Entropy Cross-entropy loss, or log loss, measures the performance of a classification model whose output is a pro...

Loss Functions Part-2

Analytics Vidhya

As we all know that for regression problems we use Least square error as the loss function. Through this, we get a convex loss function and we can optimize by finding its global minimal. But when it…

Loss Functions in Machine Learning

Towards Data Science

Understand the most common loss functions and when to use each one Continue reading on Towards Data Science

The Mathematics of Loss Functions in Machine Learning

The Pythoneers

Introduction to Loss Functions In machine learning, how well predictive models work depends largely on their ability to reduce errors in their predictions. At the heart of this process are loss funct...

What are Loss Functions?

Towards Data Science

An article explaining different most used loss function in deep learning

A Quick Guide to Loss Functions

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Types of Loss functions used in Classification and Regression problems

Machine Learning 103: Loss Functions

Towards Data Science

In two previous articles I covered two of the most basic models used in machine learning — linear regression and logistic regression. In both cases, we were interested in searching for the set of…

A Comprehensive Guide To Loss Functions — Part 1 : Regression

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Loss functions are used to calculate the difference between the predicted output and the actual output. To know how they fit into neural networks, read :

Loss Functions and Their Use In Neural Networks

Towards Data Science

Overview of loss functions and their implementations Photo by Chris Ried on Unsplash Loss functions are one of the most important aspects of neural networks, as they (along with the optimization func...

Loss Functions: An Algorithm-wise Comprehensive Summary

Daily Dose of Data Science

Loss functions are a key component of ML algorithms. They specify the objective an algorithm should aim to optimize during its training. In other words, loss functions tell the algorithm what it shoul...

Loss Functions in Neural Networks

Becoming Human: Artificial Intelligence Magazine

Loss functions show how deviated the prediction is with actual prediction. Machines learn to change/decrease loss function by moving close to the ground truth. There are many functions out there to…

Classification Loss Functions: Intuition and Applications

Towards Data Science

A simpler way to understand derivations of loss functions for classification and when/how to apply them in PyTorch Source: GPT4o Generated Whether you are new to exploring neural networks or a season...