Follow our WeChat public account “ML_NLP“ Set as “Starred“, important content delivered first-hand! Produced by Big Data Digest Compiled by: Hong Yingfei, Ning Jing PyTorch is one of the deep learning framework libraries, an open-source deep learning platform from Facebook, providing seamless connection from research prototype to production deployment. This article aims to introduce the … Read more
When I first started exploring machine learning algorithms, I was overwhelmed by all the mathematical content. I found that without fully understanding the intuition behind the algorithm, it was difficult to grasp the underlying mathematical principles. Therefore, I tend to favor explanations that break down the algorithm into simpler, more digestible steps. This is what … Read more
For most data analysts, regression models are undoubtedly one of the fundamental skills. At the beginning of this century, many investment banks used the application of regression models as a standard for evaluating analysts. For over a decade, regression models have maintained a significant presence in all analyses and predictions. However, in recent years, a … Read more
XGBoost is an excellent algorithm that has been widely used in many competitions such as Kaggle, where we can see that many winning teams utilize XGBoost and achieve outstanding performance. Currently, most classification models in practical applications are based on XGBoost, making it a very practical and user-friendly algorithm. The main reference for this article … Read more
Case Introduction This case aims to predict the Boston housing data using the XGBoost algorithm. The Boston housing dataset is a commonly used dataset for house price prediction, containing 506 samples and 13 features, including crime rates in the area, average number of rooms per dwelling, and distance to the city center. Algorithm Principle XGBoost … Read more
Concept of XGBoost XGBoost stands for “Extreme Gradient Boosting”. The XGBoost algorithm is a type of ensemble algorithm formed by combining base functions with weights, resulting in a good fitting effect on data. Unlike traditional Gradient Boosting Decision Trees (GBDT), XGBoost adds a regularization term to the loss function. Additionally, since some loss functions are … Read more
Introduction XGBoost (eXtreme Gradient Boosting) is known as extreme gradient boosting. It is the ace of ensemble learning methods, and most winners in Kaggle data mining competitions have used XGBoost. XGBoost performs exceptionally well in most regression and classification problems. This article provides a detailed introduction to the XGBoost algorithm principles. Table of Contents 1. … Read more
Source: Turing Artificial Intelligence, Aotu Data This article is about 3600 words long and suggests a reading time of 7 minutes. This article introduces the 10 most common machine learning algorithms in an illustrated manner. In the field of machine learning, there is a saying that “there is no free lunch in the world”, which … Read more
In the field of machine learning, there is a saying that “there is no free lunch in the world,” which simply 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, or … Read more
Source: Turing Artificial Intelligence Depending on the type of data, modeling a problem can be approached in different ways. In the field of machine learning or artificial intelligence, people first consider the learning method of the algorithm. There are several main learning methods in machine learning. Categorizing algorithms according to their learning methods is a … Read more