Explore >> Select a destination
|
You are here 
|
xcorr.net | ||
| | | | |
www.v7labs.com
|
|
| | | | | Learn about the different types of neural network architectures. | |
| | | | |
blog.otoro.net
|
|
| | | | | [AI summary] This article describes a project that combines genetic algorithms, NEAT (NeuroEvolution of Augmenting Topologies), and backpropagation to evolve neural networks for classification tasks. The key components include: 1) Using NEAT to evolve neural networks with various activation functions, 2) Applying backpropagation to optimize the weights of these networks, and 3) Visualizing the results of the evolved networks on different datasets (e.g., XOR, two circles, spiral). The project also includes a web-based demo where users can interact with the system, adjust parameters, and observe the evolution process. The author explores how the genetic algorithm can discover useful features (like squaring inputs) without human intervention, and discusses the ... | |
| | | | |
distill.pub
|
|
| | | | | When a neural network layer is divided into multiple branches, neurons self-organize into coherent groupings. | |
| | | | |
coornail.net
|
|
| | | Neural networks are a powerful tool in machine learning that can be trained to perform a wide range of tasks, from image classification to natural language processing. In this blog post, well explore how to teach a neural network to add together two numbers. You can also think about this article as a tutorial for tensorflow. | ||
