An artificial neural network is actually like a complex calculator; you input something, and it gives you a result. Just like when you input 2+2 into a calculator, it outputs 4, but an artificial neural network can handle more than just basic arithmetic; it can process more complex things like images, text, etc. So when … Read more
1 Algorithm Introduction Artificial Neural Networks (ANN), also known simply as neural networks, are mathematical models that closely resemble the characteristics of biological neural networks among many machine learning algorithms. ANN simulates the structure and function of biological neural networks (the brain) and is composed of numerous nodes (also called “neurons” or “units”) that are … Read more
About 8000 words, recommended reading time 20 minutes. This article introduces the mathematical principles behind artificial neural networks. Introduction When it comes to artificial intelligence algorithms, artificial neural networks (ANN) are an unavoidable topic. However, for beginners, it is often easy to be overwhelmed by the complex concepts and formulas in ANN, leading to a … Read more
Author: Matthew Stewart Translator: Che Qianzi Proofreader: Chen Dan This article is approximately 5500 words, and it is recommended to read it in 12 minutes. The knowledge in this article will provide a strong foundation to introduce you to the performance of neural networks, applied in deep learning applications. “Your brain does not generate thoughts. … Read more
Source: Machine Learning Algorithms This article is about 5000 words long, and it is recommended to read in 8 minutes This article summarizes some basic concepts about Convolutional Neural Networks (CNN). Introduction This article summarizes some basic concepts about Convolutional Neural Networks (CNN) and provides detailed explanations of the principles involved. Through this article, one … Read more
In recent years, artificial intelligence technology has developed rapidly, and deep learning technology has also advanced quickly with the improvement of computing power. At the same time, object detection is a fundamental problem in the fields of machine vision and artificial intelligence, with the main goal of accurately locating various object categories and position bounding … Read more
Introduction In April this year, Max Tegmark’s team released a brand new deep learning network structure called the Kolmogorov-Arnold Network (KAN), which quickly caused a sensation. First author Liu Ziming detailed the team’s latest work at the AI+Science reading club of the Jizhi Club (See: Liu Ziming’s Live Summary: The Capability Boundaries and Outstanding Problems … Read more
Click on the above “Beginner Learning Vision”, select to add Star or “Top” Important content delivered immediately Introduction Artificial neural networks are typically optimized through a learning method based on mathematical statistics. This article provides a detailed introduction to the definition of neural networks and the relevant operational models. Overview of Structure 1. Introduction to … Read more
Click the above “Beginner Learning Visuals” to choose to add a “Star” or “Pinned” Heavyweight content delivered first-hand Source:getwallpapers.com Deep learning is one of the important branches of machine learning. Its goal is to teach computers to perform tasks that are quite natural for humans. Deep learning is also a key technology behind autonomous vehicles, … Read more
Original Content, First Release, No Reprints In the previous articles “Understanding Neural Networks: CNN” and “Building CNN Networks with Fashion-MNIST Dataset (Including Code)”, we provided a detailed introduction to the architecture and specific implementation of CNN networks, among which the most classic CNN networks include LeNet-5, AlexNet, GoogLeNet, ResNet, etc. Today, I will explain another … Read more