<rss xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title>Terminology - Tag - Jorgen Bergstrom</title><link>https://bergstrom.org/tags/terminology/</link><description>Terminology - Tag - Jorgen Bergstrom</description><generator>Hugo -- gohugo.io</generator><language>en-us</language><copyright>Jorgen Bergstrom</copyright><lastBuildDate>Thu, 27 Feb 2025 20:18:36 -0500</lastBuildDate><atom:link href="https://bergstrom.org/tags/terminology/" rel="self" type="application/rss+xml"/><item><title>Machine Learning Terminology</title><link>https://bergstrom.org/posts/ml_terminology/</link><pubDate>Thu, 27 Feb 2025 20:18:36 -0500</pubDate><author>Jorgen Bergstrom</author><guid>https://bergstrom.org/posts/ml_terminology/</guid><description>Different Types of Neural Networks (NN) There are several types of neural networks designed to perform specific tasks or process different kinds of data. Here are some of the most popular basic types:
Feedforward Neural Networks (FFN) The simplest type of neural network, consisting of interconnected nodes. Convolutional Neural Networks (CNN) Primarily used for image and vision-related tasks such as object recognition. Reccurent Neural Networks (RRN) Designed to process sequential data, like time series, by maintaining internal state variables.</description></item></channel></rss>