loss function - Learn Data Science with Travis

What are Loss Functions?

Towards Data Science

An article explaining different most used loss function in deep learning

Most Common Loss Functions in Machine Learning

Towards Data Science

As a core element, Loss function is a method of evaluating your Machine Learning algorithm that how well it models your featured dataset. It is defined as a measurement of how good your model is in…

Loss Functions

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 in Machine Learning

Towards Data Science

Loss functions have an important role in machine learning as they guide the learning process of the model and define its objective. There is a large number of loss functions available and choosing…

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…

How to Create a Custom Loss Function | Keras

Towards Data Science

The Loss Function is one of the important components of Neural Network. Loss is nothing but a prediction error of Neural Net. And the method to calculate the loss is called Loss Function. Loss is…

A Single Frame Summary of 10 Most Common Regression and Classification Loss Functions

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...

Implementing Custom Loss Functions in PyTorch

Towards Data Science

In machine learning, the loss function is a critical component that measures the difference between the predicted output and the actual output. It plays a vital role in the training of a model, as it…...

NLP using Deep Learning Tutorials : Understand Loss Function

Towards AI

Loss function also called the objective function, is one of the main bricks in supervised machine learning algorithm which is based on labeled data. A loss function guides the training algorithm to…

Built-in loss functions

Codecademy

In PyTorch, loss functions are critical in the training process of deep learning models. They measure how well the model’s predictions match the ground truth. PyTorch provides several built-in loss fu...

Loss Functions -when to use which one

Towards Data Science

The ultimate goal of all algorithms of machine learning is to decrease loss. Loss has to be calculated before we try strategy to decrease it using different optimizers. Loss Function is an error in 1…...