Machine learning is a hot topic, but apart from the teachers who know it well, very few people can explain what it’s all about. If you read articles about machine learning online, you’re likely to encounter one of two situations: either a heavy academic trilogy filled with various theorems (I struggle to grasp even half … Read more
Machine learning is divided into two main categories based on model types: supervised learning models and unsupervised learning models. 1. Supervised Learning Supervised learning typically uses training data with expert-labeled tags to learn a function mapping from input variable X to output variable Y. Y = f(X), where training data is usually in the form … Read more
Source: dataxon Translator: Ahong Everyone is talking about machine learning, but very few people can explain what it really is, apart from the teachers who know it inside out. If you read articles about machine learning online, you are likely to encounter two scenarios: heavy academic tracts filled with various theorems (I struggle to grasp … Read more
Machine learning is a hot topic, but aside from the experts, very few people can explain it clearly. If you read articles about machine learning online, you are likely to encounter two situations: heavy academic works filled with various theorems (I can barely handle half a theorem), or dazzling stories about artificial intelligence, data science … Read more
Machine learning is a topic everyone is talking about, but apart from those who are well-versed in it, very few can explain what it’s all about. If you read articles about machine learning online, you’re likely to encounter two scenarios: dense academic treatises filled with various theorems (I struggle to grasp half a theorem), or … Read more
About 10,000 words, recommended reading time 20 minutes. This article introduces the models of machine learning. Machine learning is the process of allowing computers to automatically extract rules and patterns from data, thereby completing specific tasks. According to model types, machine learning is mainly divided into three categories: supervised learning models, semi-supervised learning, and unsupervised … Read more
Source: DeepHub IMBA This article is about 4300 words long and takes approximately 12 minutes to read. This is an attempt to build a Gaussian Mixture Model (GMM) classifier using Pytorch. We will build the Gaussian Mixture Model (GMM) from scratch. This will give us a basic understanding of the GMM, and this article will … Read more
Reprinted from:Author: james_aka_yale In the field of machine learning, there is a saying: “There is no free lunch in the world,” which means that no single algorithm can perform best on every problem. This theory is particularly important in supervised learning. For example, you cannot say that neural networks are always better than decision trees, … Read more
Recently, I was preparing some materials on machine vision and implemented a small case while writing code. You can try implementing it yourself. # Import modules import ddddocr # Call the method from the module p=ddddocr.DdddOcr() # Open the image to be recognized with open('picture/img_1.png','rb') as file: # Pass the data stream and store: ddos … Read more
This article is reprinted from the public account Xinkou Dushuo KNN is a fundamental data classification algorithm in machine learning. Here, I will explain its utility through a story. Let’s start with a joke. During a matchmaking event, a beautiful girl asked the young man: Do you have a three-bedroom apartment? The young man: No. … Read more