Produced by Big Data Digest Author: Jiang Baoshang Many students, after starting with machine learning, directly use TensorFlow to implement neural networks, with little understanding of the underlying mechanisms of neural networks. Programming languages and frameworks evolve rapidly, so understanding the principles behind them is essential. Below, we will implement a neural network step by … Read more
Click the top to follow us! XGBoost Feature Engineering: From Beginner to Expert Recently, I’ve been diving into XGBoost and found that feature engineering is indeed a profound subject. This thing can be said to be the lifeline of model performance; if done poorly, all efforts can be in vain. Today, let’s chat about the … Read more
Hello everyone! Niu Ge is back! Today we are going to talk about a very powerful machine learning library – XGBoost. When it comes to it, we must mention its dominance in major data competitions. It’s like the “timely rain Song Jiang” in the machine learning world, always able to help you improve model performance … Read more
XGBoost: A Powerful Python Library for Extreme Gradient Boosting Li: Wang, I often feel that my efficiency in data processing and predictive modeling is not high. Is there a good Python library that can help me? 😟 Wang: Of course! 🙌 Today, I will introduce you to XGBoost, which is a great assistant in the … Read more
XGBoost: A Super Useful Python Library! XGBoost is quite renowned in the machine learning community! It’s particularly useful for data mining and predictions. Why? Because it’s accurate! And it’s fast! Today, I’ll chat with you about XGBoost, ensuring you understand it right away! What is XGBoost? XGBoost, short for Extreme Gradient Boosting, sounds quite mysterious, … Read more
XGBoost has shone in Kaggle competitions. In previous articles, the principles of the XGBoost algorithm and the XGBoost splitting algorithm were introduced. Most explanations of XGBoost parameters online only scratch the surface, making it extremely unfriendly for those new to machine learning algorithms. This article will explain some important parameters while referring to mathematical formulas … Read more
Hello everyone, today let’s talk about XGBoost~ XGBoost (Extreme Gradient Boosting) is particularly suitable for variants of Gradient Boosting Decision Trees. It was proposed by Tianqi Chen in 2016 and has been widely popular in machine learning competitions such as Kaggle. The historical background of XGBoost can be traced back to the Gradient Boosting algorithm, … Read more
XGBoost: The Python Tool for Gradient Boosting! Hello everyone! Today I want to share with you a super powerful tool in the field of machine learning—XGBoost. I still remember when I first participated in a Kaggle competition, I noticed that almost all winning solutions used XGBoost, which sparked my strong interest in it. XGBoost is … Read more
Core Points:From Principles to Cases, A Complete Summary of XGBoost! Hello, I am Cos Dazhuang~ Recently, many people have been messaging about XGBoost, feeling it’s very useful but still somewhat unclear. Today, we will clarify it from principles, derivation of formulas, to a practical case at the end, hoping it helps! In simple terms, XGBoost … Read more
Hello everyone, today we will discuss Generative Adversarial Networks, and how to create anime avatars. In this lesson, we will design and implement a Convolutional Generative Adversarial Network (DCGAN): Then we will use this network to generate various anime avatars. 1. What Are Generative Adversarial Networks Generative Adversarial Networks, abbreviated as GAN. GAN is an … Read more