Click the blue text to follow us for more knowledge sharing. 01 Forward Propagation To explain the forward propagation of neural networks, we will use a simple fully connected three-layer neural network as shown in the figure below: The neural network consists of layers of neurons (one column is considered a layer of the neural … Read more
The winter break has begun, and Science Popularization China has specially launched a series of popular science content about technology and Artificial Intelligence (AI), hoping to introduce the mysteries of these cutting-edge technologies in an easy-to-understand manner. From basic concepts to practical applications, from historical development to future trends, children can appreciate the charm of … Read more
Source: Yunqi Community This article contains 6500 words and is recommended to be read in 10 minutes. Starting from the historical development of neural networks, this article introduces the perceptron model, feedforward neural networks, and the BP algorithm. [Introduction] What comes to mind when you think of neural networks? Have you ever pondered the principles … Read more
Basic Mathematical Principles The main differences in artificial neural network models lie in the topology of the neural network connections, the characteristics of the neurons, and the scale of learning, etc. Based on the differences in the topology of neuron connections, we can roughly categorize neural network models into the following two types. 1. Feedforward … Read more
Source | Network One thing that might surprise beginners is that neural network models are not complex! The term ‘neural network’ sounds impressive, but in fact, neural network algorithms are simpler than people think. This article is entirely prepared for beginners. We will understand the principles of neural networks by implementing one from scratch using … Read more
Table of Contents 1. Neuron Model 2. Perceptron and Neural Networks 3. Error Backpropagation Algorithm 4. Common Neural Network Models 5. Deep Learning 6. References Currently, deep learning (Deep Learning, referred to as DL) is exceptionally popular in the field of algorithms, not only in the internet and artificial intelligence but also in various fields … Read more
Madio.net Mathematics China Reprinted from:Author丨Mountain and Water You and Me @ Zhihu Source丨https://zhuanlan.zhihu.com/p/468100301 Editor丨Extreme City Platform Currently, building a Convolutional Neural Network (CNN) is generally done directly using deep learning frameworks such as Pytorch or Tensorflow, which is quite simple. However, if you’re writing the backpropagation process from scratch, it is much more complicated than … Read more
Author: Nan Ke Yi Meng Ning Chen Lun @ Zhihu (Authorized) Editor: Jishi Platform Source: https://zhuanlan.zhihu.com/p/61898234 The mathematical derivation of backpropagation in multilayer perceptrons is mainly represented using mathematical formulas. In fully connected neural networks, these are not complicated, and even purely mathematical formulas are relatively easy to understand.However, convolutional neural networks are relatively more … Read more
Click the blue text above to follow ↑↑↑↑↑ Author: Andrey Kurenkov As the puzzle of training multi-layer neural networks is unraveled, this topic has once again become extraordinarily popular, and Rosenblatt’s lofty ambitions seem to be realized. Until 1989, another key discovery was published, which is still widely cited in textbooks and major lectures. Multi-layer … Read more
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