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
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
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
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
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
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
Click the above“Beginner Learning Vision” to select “Star” or “Pin” Heavyweight content delivered first-hand Introduction In recent years, there has been increasing interest in extending deep learning methods to graphs. Driven by multiple factors, researchers have drawn on ideas from convolutional networks, recurrent networks, and deep autoencoders to define and design neural network structures for … Read more
Author: Chen Zhiyan This article is about 2000 words long and is recommended to be read in 5 minutes. This article will help you understand <strong>convolutional neural networks</strong>.
Source: AI Youdao Extreme Market Platform This article is approximately 5900 words long and is recommended for a reading time of 10 minutes. This article will provide a brief summary from a more intuitive perspective of the currently classic and popular GNN networks, including GCN, GraphSAGE, GAT, GAE, and graph pooling strategies like DiffPool, etc. … Read more
Source: 36 Big Data This article is 8000 words long and is recommended to be read in 12 minutes. This article organizes and introduces neural network architectures for you. As new neural network architectures emerge constantly, it is quite challenging to document all neural networks. Understanding all the networks represented by these abbreviations (DCIGN, IiLSTM, … Read more