Understanding XGBoost and Boosted Trees

Understanding XGBoost and Boosted Trees

Author: Tianqi Chen, graduated from Shanghai Jiao Tong University ACM class, currently studying at the University of Washington, engaged in large-scale machine learning research. Note: truth4sex 1. Introduction At the invitation of @Longxing Biaoju, I am writing this article. As a very effective machine learning method, Boosted Trees are one of the most commonly used … Read more

Understanding Machine Learning in Simple Terms

Understanding Machine Learning in Simple Terms

This article is reprinted from the public accountDatawhale Translator:Ahong, Source:dataxon Machine learning is a hot topic, but aside from those who are well-versed in it, very few can explain what it really is. When reading articles about machine learning online, you are likely to encounter two situations: either a heavy academic trilogy filled with various … Read more

An Introduction to Machine Learning in Simple Terms

An Introduction to Machine Learning in Simple Terms

Machine learning is a topic everyone is discussing, but aside from teachers who have a deep understanding, very few can explain what it is clearly. If you read articles about machine learning online, you are likely to encounter two scenarios: dense academic texts filled with various theorems (I can barely handle half a theorem) or … Read more

A Review of Interpretability Research in Convolutional Neural Networks

A Review of Interpretability Research in Convolutional Neural Networks

Welcome to click the blue text to follow “Smart IT Journal“! Dou Hui, Zhang Lingming, Han Feng, Shen Furao, Zhao Jian Journal of Software Journal of Software Abstract The performance of neural network models is increasingly powerful and widely applied to solve various computer-related tasks, demonstrating excellent capabilities. However, humans do not fully understand the … Read more

Three Steps of Machine Learning

Three Steps of Machine Learning

Machine learning can be approximately equated to finding a functional function f related to specific inputs and expected outputs through statistical or inferential methods within data objects (as shown in Figure 1). Usually, we denote the input variable (feature) space as uppercase X and the output variable space as uppercase Y. Therefore, machine learning can … Read more

The Lazy Algorithm – KNN

The Lazy Algorithm - KNN

Total Article 77 This article introduces one of the most basic and also the most “lazy” algorithms in machine learning – KNN (k-nearest neighbor). Do you know why it is called the laziest? 01|Algorithm Introduction: KNN is short for k-nearest neighbor, which indicates the K closest points. This algorithm is commonly used to solve classification … Read more

Introduction to Python Data Mining and Machine Learning (With Code and Examples)

Introduction to Python Data Mining and Machine Learning (With Code and Examples)

Author: Wei Wei Source:Python Enthusiasts Community This article contains a total of 7800 words, and it is recommended to read for 10+ minutes. This article combines code examples to help you get started with Python data mining and machine learning techniques. This article includes five knowledge points: 1. Introduction to data mining and machine learning … Read more