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
Machine learning is essentially a search in space and generalization of functions. Now enterprises mainly rely on supervised learning based on samples. In reality, logistic regression (LogisticRegression, LR) has a fast training speed and strong interpretability, but its fitting accuracy is insufficient. On the other hand, support vector machines (SupportVectorMachine, SVM) have high prediction accuracy, … Read more
Without high-quality data, there are no high-quality data mining results. Missing data values are one of the common issues encountered in data analysis. When the proportion of missing data is very small, missing records can be directly discarded or handled manually. However, in actual data, missing data often accounts for a significant proportion. In this … Read more
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
Source: Not Just Data Analysis This article is about 5800 words long, and it is recommended to read for over 10 minutes. Without statistics, machine learning cannot exist, but due to the contemporary information explosion and the vast amount of data humans can access, machine learning is extremely useful. The distinction between statistics and machine … Read more
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
All algorithms in machine learning rely on minimizing or maximizing a function, which we call the “objective function.” The function that is minimized is called the “loss function,” which measures the model’s ability to predict the expected outcome. The most commonly used method for minimizing the loss function is the “gradient descent method.” You can … Read more
Click on the above “Beginner Learning Vision”, and select to add a “Star Mark” or “Top” Heavyweight content delivered promptly 【Guide】Hello everyone, I am Yongyu. A coder who enjoys exploring and sharing AI knowledge! Regression analysis provides a solid foundation for many machine learning algorithms.In this article, we will introduce the concept of regression analysis, … Read more
Source: AI Technology Review, DataPi THU This article is about 7100 words long and is recommended for a 13-minute read. It summarizes the historical origins of several foundational algorithms in the field of machine learning. Recently, Andrew Ng updated a blog post on his founded AI Weekly, “The Batch”, summarizing the historical origins of several … Read more
Today, let’s learn how to use the lazypredict library, where we can implement many ML models on our dataset with just one line of code, allowing us to briefly understand which models suit our dataset. Step 1 Install the lazypredict library using the following method: pip install lazypredict Step 2 Import pandas to load our … Read more