Source: Algorithm Advancement This article is approximately 4800 words long and is suggested to be read in 8 minutes. This article introduces the functionality of neural networks. In the fields of machine learning and related areas, artificial neural networks are computational models inspired by biological neural networks: each neuron is connected to other neurons, and … Read more
Original Title | Gentle Dive into Math Behind Convolutional Neural Networks
Author: Chen Zhiyan This article is about 2500 words long and is recommended for a 7-minute read. The future of neurons is full of infinite possibilities. Introduction In this era of information explosion, have you ever dreamed of conversing fluently with machines or having AI assist you in crafting stunning articles? All of this relies … Read more
To date, a major concern regarding neural networks is that they are difficult to interpret black boxes. This article primarily aims to understand theoretically why neural networks perform so well in pattern recognition and classification. The essence lies in the fact that they distort and transform the original input through layers of affine transformations and … Read more
Why is Machine Learning Necessary? Some tasks are complex to encode directly; we cannot handle all the nuances and simple coding. Therefore, machine learning is essential. Instead, we provide a large amount of data to machine learning algorithms, allowing them to explore the data and build models to solve problems. For example: recognizing 3D objects … Read more
Neural networks are an important machine learning technology. They form the basis of the currently hottest research direction—deep learning. Learning about neural networks not only allows you to master a powerful machine learning method but also helps you better understand deep learning technologies. This article explains neural networks in a simple, step-by-step manner, suitable for … 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
In today’s internet age, the intricate big data and network environment pose significant challenges to traditional information processing theories, artificial intelligence, and artificial neural networks.In recent years, deep learning has gradually come into people’s view, with an increasing number of cases solving various problems through deep learning.Some traditional image processing techniques can also achieve superior … Read more
Datawhale Insights Compiled by: Wang Xiaoxin, Source: Quantum Bits When adjusting the model’s weight and bias update methods, 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 algorithms … Read more
Source: Light Wave Common Original Author: Qiu Zhecheng The brain can be considered the most complex biological structure on Earth, with a convoluted network of neurons that enables it to process information, control bodily functions, and support consciousness and thought activities. Based on this, scientists proposed the concepts of neuron models and neural networks. However, … Read more