Evolving Neural Networks

Evolving Deep Neural Networks

Towards Data Science

Deep learning architectures are getting harder to design, but evolutionary algorithms may help us overcome this. This review presents important recent research in this matter.

Towards Data Science

For the past decade, deep learning has dominated the machine learning landscape, often to the exclusion of other techniques. As a data scientist, it’s important to have a variety of tools at your…

The Evolution of Neural Networks: Kolmogorov-Arnold Networks

Level Up Coding

Introduction K olmogorov–Arnold Networks (KANs) are an innovative approach to neural networks, inspired by the Kolmogorov-Arnold representation theorem. Unlike traditional Multi-Layer…

New to Neural Networks?

Analytics Vidhya

Neural Networks have been around for a while now. Warren McCulloh and Walter Pitts wrote a paper all the way back in 1943 pondering the inner workings of neurons in animals and proposed a way to…

Two Fundamental Neural Network Anatomical Structures

Towards Data Science

Like other organisms, artificial neural networks have evolved through the ages. In this post, we cover two key anatomies that have emerged: fully-connected versus convolutional. The second one is…

Using the metrics behind the Neural Networks for predicting software evolution

Towards Data Science

The Asimov Institute had publish this post showing us the different kinds of networks shown in the picture below. Neural networks are hot now, but the idea of representing knowledge in this way come…

Neural Networks From the Ground Up (Part 1)

Towards Data Science

Everyone knows that neural networks are amazing. In the past two decades neural nets have gone from an experimental method to the most widely used machine learning technique we have today. It’s also…

Unit 3 Application) Evolving Neural Network for Time Series Analysis

Towards Data Science

Hello and Welcome back to this full course on Evolutionary Computation! In this post we will wrap up Unit 3 with the much anticipated application of evolving the weights of a Neural Network for Time…

Neuroevolution — evolving Artificial Neural Networks topology from the scratch

Becoming Human: Artificial Intelligence Magazine

This article presents how to build and train Artificial Neural Networks by NEAT algorithm. It will consider weakness of current Gradient Descent based training methods and shows a way to improve it.

An Introduction to Artificial Neural Networks

Towards Data Science

Artificial Neural Network (ANN) is a deep learning algorithm that emerged and evolved from the idea of Biological Neural Networks of human brains. An attempt to simulate the workings of the human…

Breaking neural networks with adversarial attacks

Towards Data Science

As many of you may know, Deep Neural Networks are highly expressive machine learning networks that have been around for many decades. In 2012, with gains in computing power and improved tooling, a…

Neural Networks

Codecademy

Artificial neural networks (ANN) are a method in artificial intelligence that teaches computers to process data in a way similar to the human brain. What Is An Artificial Neural Network (ANN) An ANN a...