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
Have you noticed that neural networks are everywhere? They appear in the news, in your phone, and even on your social media. But honestly, most of us don’t know how they work. Those fancy math and strange terms like “backpropagation”? In this article, we explore the Multi-Layer Perceptron (MLP) – the most basic type of … Read more
Click on the above“Beginner Learning Vision” to select “Star” or “Top“ Important content delivered promptly Source:Machine Heart For academic sharing only, please contact for deletion if infringing Despite the widespread success of DNNs in various practical applications, their processes are often viewed as black boxes because it is difficult to explain how DNNs make decisions. … Read more
1. What is a Neural Network? A neural network (Neural Networks, abbreviated as NN), also known as an artificial neural network (ANN) or simulated neural network (SNN), is a subset of machine learning (ML, Machine Learning) and is the core of deep learning (DL, Deep Learning) algorithms. Its name and structure are inspired by the … Read more
1 Algorithm Introduction Convolutional Neural Networks (CNNs) are a class of feedforward neural networks that include convolutional computations and have a deep structure. They have emerged in recent years as an efficient recognition method that has gained widespread attention. The design inspiration for CNNs comes from the hierarchical processing capabilities of the animal visual system, … Read more