Principles of Neural Network Algorithms in Deep Learning Graphical Parameter Calculation Junior High Mapping Neural Network Mapping? What is a Neural Network Algorithm? Parameter Solving References What is a Neural Network Algorithm? Junior High Mapping In junior high school, we learned about mapping with the equation y = f(x). By using several pairs of values … Read more
In recent years, artificial intelligence has developed rapidly, gradually penetrating various industries and fields. More and more people are learning AI-related technologies. To help beginners quickly grasp the basic principles of AI, Professor Ma Shaoping, Vice Chairman of CAAI, has written an introductory book titled “How Computers Achieve Intelligence.” Through the new popular science column … Read more
Madio.net Mathematics China ///Editor: Only tulips’ garden Neural networks are a clever combination of linear and nonlinear modules. When we wisely choose and connect them, we have a powerful tool to approximate any mathematical function. For example, using nonlinear decision boundaries for classification. The backpropagation technique is responsible for updating the trainable parameters. Although it … Read more
Source: PaperWeekly This article is about 4600 words long, and it is recommended to read it in 10 minutes. This article analyzes the reversible residual networks as the basis. Why Use Reversible Networks? Because both encoding and decoding use the same parameters, the model is lightweight. The reversible denoising network InvDN has only 4.2% of … Read more
So far, a major concern about neural networks is that they are difficult to interpret black boxes. This article primarily explains theoretically why neural networks perform so well in pattern recognition and classification. Essentially, they distort and transform the original input through layers of affine transformations and nonlinear transformations until different categories can be easily … Read more
Essentially, deep learning is a trendy new term derived from a topic that has existed for quite some time – neural networks. >>>> Since the 1940s, deep learning has developed rapidly, achieving great success and being widely used in smartphones, cars, and many other devices. So, what are neural networks, and what can they do? … Read more
Source:AI 有道 Approximately 3200 words, recommended reading time 5 minutes This article introduces the mathematical principles behind neural networks. Neural networks are a clever arrangement of linear and nonlinear modules. By smartly selecting and connecting these modules, we obtain a powerful tool to approximate any mathematical function, such as a neural network that can classify … Read more
Have you noticed that neural networks are everywhere? They appear in the news, in your phone, and even on your social media. But honestly, most of us don’t know how they work. Those fancy math and strange terms like “backpropagation”? In this article, we explore the Multi-Layer Perceptron (MLP) – the most basic type of … Read more
Author: Zhang Jianzhong Source: http://blog.csdn.net/zouxy09/article/details/8775518 Deep learning is a new field in the study of machine learning, motivated by the establishment and simulation of neural networks that analyze and learn like the human brain. It mimics the mechanisms of the human brain to interpret data such as images, sounds, and text. Deep learning is a … Read more
(Click the public account above, you can quickly follow) Source: Poll’s Notes cnblogs.com/maybe2030/p/5597716.html If you have good articles to submit, please click → here for details Table of Contents 1. Neuron Model 2. Perceptron and Neural Networks 3. Backpropagation Algorithm 4. Common Neural Network Models 5. Deep Learning 6. References Currently, deep learning (Deep Learning, … Read more