Neural Network Analysis Algorithm

Neural Network Analysis Algorithm

Algorithm Origin In cognitive science, human brain thinking is divided into three basic modes: logical thinking, intuitive thinking, and inspirational thinking. The neural network uses its algorithm characteristics to simulate the second mode of human brain thinking. It is a nonlinear dynamic system characterized by distributed information storage and parallel collaborative processing. Although the structure … Read more

5 Common Derivatives of Neural Networks with Detailed Formula Process

5 Common Derivatives of Neural Networks with Detailed Formula Process

Author: Criss Source: Machine Learning and Generative Adversarial Networks 01 Derivative of Softmax 1.1 Derivative of Softmax Generally, the last layer of a classification model is the softmax layer. Assuming we have a classification problem, the structure of the corresponding softmax layer is shown in the figure below (it is generally considered that the output … Read more

Principles of Neural Network Algorithms in Deep Learning

Principles of Neural Network Algorithms in Deep Learning

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

Understanding Neural Network Training: A Comprehensive Guide

Understanding Neural Network Training: A Comprehensive Guide

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

6 Methods for Compressing Convolutional Neural Networks

6 Methods for Compressing Convolutional Neural Networks

This articleis approximately 5200 words, recommended reading time is10+minutes We know that, to some extent, the deeper the network, the more parameters it has, and the more complex the model, the better its final performance. The compression algorithm for neural networks aims to transform a large and complex pre-trained model into a streamlined smaller model. … Read more

Top 10 Deep Learning Algorithms

Top 10 Deep Learning Algorithms

Since the concept of deep learning was proposed in 2006, almost 20 years have passed. As a revolution in the field of artificial intelligence, deep learning has given rise to many influential algorithms. So, what do you think are the top 10 deep learning algorithms? Here are my top 10 deep learning algorithms, which hold … Read more

Illustrated Efficient Neural Architecture Search (ENAS)

Illustrated Efficient Neural Architecture Search (ENAS)

Click on the above “Beginner’s Guide to Vision” to select and add Star or Pin. Important content delivered in real-time This article is translated from: [Illustrated: Efficient Neural Architecture Search] https://towardsdatascience.com/illustrated-efficient-neural-architecture-search-5f7387f9fb6 (Requires VPN) Introduction Designing neural network architectures for different tasks, such as image classification and natural language understanding, usually requires extensive structural engineering and … Read more

Understanding the Relationship Between CNN and RNN

Understanding the Relationship Between CNN and RNN

Source: Artificial Intelligence AI Technology This article is about 6000 words long and is recommended to read in 12 minutes. This article introduces your understanding of CNN and RNN. This article mainly focuses on understanding CNN and RNN, summarizing their advantages through comparison while deepening one’s understanding of this area of knowledge. The code references … Read more

Don’t Overlook Graph Neural Networks (GNN) in 2023!

Don't Overlook Graph Neural Networks (GNN) in 2023!

Introduction Graph Neural Networks (GNN) — a dark horse among various neural networks. It is widely applicable across various fields, including recommendation systems, Google Maps traffic prediction, drug discovery, protein discovery, and more. To explore the development and real-world applications of graph neural networks in algorithmic neural solving, the Intelligence Club, in collaboration with Associate … Read more

BP Neural Network: An Iterative Network That Continuously Improves

BP Neural Network: An Iterative Network That Continuously Improves

1 Algorithm Introduction From the name, we can see that the BP neural network can be divided into two parts: bp and neural network. Here, bp is the abbreviation for Back Propagation, which means reverse propagation. The BP network can learn and store a large number of input-output mapping relationships without needing to reveal the … Read more