Dimensionality Reduction

Comparison Summary of 10 Nonlinear Dimensionality Reduction Techniques in Machine Learning

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Comparison Summary of 10 Nonlinear Dimensionality Reduction Techniques in Machine Learning

Approximately 3800 words, recommended reading time 6 minutes. This article introduces 10 nonlinear dimensionality reduction techniques in machine learning. Dimensionality reduction means reducing the number of features in a dataset without losing too much information. Dimensionality reduction algorithms fall under the category of unsupervised learning, training algorithms with unlabeled data. Although there are many types … Read more

Understanding CNN (Convolutional Neural Network) Algorithm

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This article will explain what problems CNN solves,the principles of human vision,the basic principles of CNN,The typical CNN and its practical applications in four aspects, helping you to understand Convolutional Neural Networks (CNN) in one article. 1.What Problems CNN Solves There are two major challenges in image processing: Huge Data Volume: Images are composed of … Read more

Summary of Dimensionality Reduction Algorithms in Machine Learning

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Summary of Dimensionality Reduction Algorithms in Machine Learning

Source: Algorithm Advancement This article is about 7500 words long and is recommended for a 10-minute read. It provides an information table of seven algorithms, summarizing the parameters and main objectives of each algorithm, and introduces some basic concepts of dimensionality reduction. Recently, I have been looking into some dimensionality reduction algorithms. This article first … Read more

Principles, Process, and Applications of Image Recognition

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Principles, Process, and Applications of Image Recognition

Source | Global Artificial Intelligence (ID:aicapital) Image recognition technology is an important technology in the information age, aimed at allowing computers to replace humans in processing large amounts of physical information. With the development of computer technology, human understanding of image recognition technology has deepened. The process of image recognition technology is divided into information … Read more

Understanding Word2Vec Through Visuals

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Understanding Word2Vec Through Visuals

Reference Article: https://www.jianshu.com/p/471d9bfbd72f Before understanding word2vec, we first need to grasp what One-Hot encoding is, as this simple encoding method is quite useful for handling enumerable features. Encoding One-Hot encoding, also known as single valid encoding, uses an N-bit state register to encode N states, where each state has its own independent register bit, and … Read more

Analysis of PCA and Its Application in Image Recognition

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Analysis of PCA and Its Application in Image Recognition

Principal Component Analysis (PCA) is a “frequent visitor” in the field of data analysis, much like Zhuge Liang from the Three Kingdoms period, who always skillfully arranges troops on the “battlefield” of data, simplifying complexity. Its core idea is to project the original data onto a new coordinate system through linear transformation, maximizing the variance … Read more