cover of episode Why Quadratic Cost Functions Are Ineffective in Neural Network Training

Why Quadratic Cost Functions Are Ineffective in Neural Network Training

2024/6/4
logo of podcast Machine Learning Tech Brief By HackerNoon

Machine Learning Tech Brief By HackerNoon

Frequently requested episodes will be transcribed first

Shownotes Transcript

This story was originally published on HackerNoon at: https://hackernoon.com/why-quadratic-cost-functions-are-ineffective-in-neural-network-training). Explore why quadratic cost functions hinder neural network training and how cross-entropy improves learning efficiency in deep learning models.
Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning). You can also check exclusive content about #deep-learning), #neural-networks), #what-is-cross-entropy), #sigmoid-activation-function), #neural-network-training), #quadratic-cost-function), #cross-entropy-cost-function), #hackernoon-top-story), and more.

        This story was written by: [@varunnakra1](https://hackernoon.com/u/varunnakra1)). Learn more about this writer by checking [@varunnakra1's](https://hackernoon.com/about/varunnakra1)) about page,
        and for more stories, please visit [hackernoon.com](https://hackernoon.com)).
        
            
            
            One of the most common question asked during deep learning knowledge interviews is - “Why can’t we use a quadratic cost function to train a Neural Network?**” We will delve deep into the answer for that. There will be a lot of Math involved but nothing crazy! and I will keep things simple yet precise.