Overview of Convolutional Neural Networks (CNN)

Overview of Convolutional Neural Networks (CNN)

Click on the above “Beginner Learning Vision”, choose to add Star or “Top” Essential insights delivered at the first moment Contents: 1. Concept of Convolutional Neural Networks 2. Characteristics of Convolutional Neural Networks 2.1 Local Region Connections 2.2 Weight Sharing 2.3 Downsampling 3. Structure of Convolutional Neural Networks 3.1 Convolutional Layer 3.2 Pooling Layer 4. … Read more

What Is An Artificial Neural Network?

What Is An Artificial Neural Network?

Abstract The brain controls everything we do; it is more powerful than any computer. This complex organ continuously transmits and analyzes information through neurons, even while we sleep. Scientists are trying to create a “digital brain” by understanding the brain’s functions. Can computers achieve the functionality of the human brain? To make this happen, scientists … Read more

Summary of Neural Network Optimization Algorithms

Summary of Neural Network Optimization Algorithms

Datawhale Insights Compiled by: Wang Xiaoxin, Source: Quantum Bit When adjusting the way models update weight and bias parameters, have you considered which optimization algorithm can yield better and faster results for the model? Should you use Gradient Descent, Stochastic Gradient Descent, or the Adam method? This article introduces the main differences between various optimization … Read more

Basic Principles of Neural Networks and Implementation in Python

Basic Principles of Neural Networks and Implementation in Python

1. Basic Principles of Neural Networks 1. Simple Principles of Biological Neural Networks In biological neural networks, each neuron’s dendrite receives electrical signals from multiple previous neurons, combining them into a stronger signal. If the combined signal is strong enough and exceeds the threshold, the neuron will be activated and will also send out a … Read more

The Development History of Neural Networks

The Development History of Neural Networks

First, let’s visually perceive the status of “Deep Learning”. The image below is a relationship diagram of AI, Machine Learning, and Deep Learning. The field of AI is relatively broad, Machine Learning is a subfield of AI, and Deep Learning is a subset within the Machine Learning domain. Deep learning algorithms have recently become increasingly … Read more

Simple Preferences of Neural Networks

Simple Preferences of Neural Networks

MLNLP community is a well-known machine learning and natural language processing community, covering domestic and international NLP graduate students, university teachers, and corporate researchers. The Vision of the Community is to promote communication and progress between the academic and industrial circles of natural language processing and machine learning at home and abroad, especially for beginners. … Read more

Performance Optimization of Convolutional Neural Networks

Performance Optimization of Convolutional Neural Networks

Click on the above “Beginner Learning Vision” to choose to add Starred or “Top” Heavy content delivered at the first time Author丨Li Ming Huai Jin Source|https://zhuanlan.zhihu.com/p/80361782 Editor丨Extreme City Platform Extreme City Guide This article first defines the concept of Convolutional Neural Networks, briefly introduces several common optimization methods, and discusses the author’s experiences in this … Read more

Overview of Graph Attention Networks (GAT)

Overview of Graph Attention Networks (GAT)

Author: Deng Yang This article is approximately 6300 words long and is recommended for a 10-minute read. This article briefly introduces the working principles of GAT based on the order discussed in the paper by Velickovic et al. (2017). When numbers are intangible, intuition is sparse; when forms are few, it is hard to delve … Read more

Third Generation Neural Network Models: Spiking Neural Networks for AI Applications

Third Generation Neural Network Models: Spiking Neural Networks for AI Applications

Introduction In 1997, computer scientist Wolfgang Maass proposed that networks composed of spiking neurons—spiking neural networks (SNN)—would become the “third generation of neural network models” following artificial neural networks. As one of the forefront intersections of neuroscience and artificial intelligence, the research on spiking neural networks starts from the biological rationale of neuron nodes and … Read more

Composition and Explanation of Convolutional Neural Network Structure

Composition and Explanation of Convolutional Neural Network Structure

Click on the above“Learning Visuals for Beginners” to choose to addStar Mark or “Pin to Top” Important content delivered immediately The convolutional neural network is a deep network structure mainly composed of convolutional layers. The network structure includes convolutional layers, activation layers, BN layers, pooling layers, FC layers, loss layers, etc. The convolution operation is … Read more