Well, if you think about a generic loss function with only one weight, the graphic representation will be something like…

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## Extending PyTorch with Custom Activation Functions

Extending PyTorch with Custom Activation FunctionsA Tutorial for PyTorch and Deep Learning BeginnersAlexandra DeisBlockedUnblockFollowFollowingJun 27IntroductionToday deep learning is going viral…

Continue Reading## Comprehensive Introduction to Neural Network Architecture

Comprehensive Introduction to Neural Network ArchitectureA detailed overview of neural architecture, activation functions, loss functions, output units. Matthew Stewart, PhD ResearcherBlockedUnblockFollowFollowingJun…

Continue Reading## Deep Neural Networks from scratch in Python

The network can be applied to supervised learning problem with binary classification. Figure 1. Example of neural network architectureNotationSuperscript [l]…

Continue Reading## Neural Network Activation Function Types

Neural Network Activation Function TypesUnderstanding what really happens in a neural networkFarhad MalikBlockedUnblockFollowFollowingMay 18This article aims to explain how the activation functions…

Continue Reading## Why Data should be Normalized before Training a Neural Network

Why Data should be Normalized before Training a Neural NetworkAnd Why Tanh Generally Performs Better Than SigmoidTimo StöttnerBlockedUnblockFollowFollowingMay 16Photo by Clint Adair…

Continue Reading## Google and OpenAI Help You See What Neural Networks See

Google and OpenAI Help You See What Neural Networks SeeJesus RodriguezBlockedUnblockFollowFollowingMar 7Interpretability is one of the biggest challenges of deep neural…

Continue Reading## HandCrafting an Artificial Neural Network

HandCrafting an Artificial Neural NetworkIn this article, I have implemented a fully vectorized code for Artificial Neural Network with Dropout and…

Continue Reading## A Gentle Introduction to the Rectified Linear Activation Function for Deep Learning Neural Networks

In a neural network, the activation function is responsible for transforming the summed weighted input from the node into the…

Continue Reading## How would we find a better activation function than ReLU?

Then it adds a bias, b, to that sum to arrive at a final value — that’s what that Σ symbol means.…

Continue Reading## Activation Functions in Neural Networks

It is not to scale but we can determine the error terms are reduced as learning is happening at an…

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