K-nearest neighbor (KNN) is one of the most popular algorithms in machine learning, widely used in both supervised and unsupervised learning. In supervised learning, KNN is used to calculate the distance to k neighbors and can define outliers. In unsupervised learning, KNN is also used to calculate the distances to neighbors and then define outliers. … Read more
Python Tribe (python.freelycode.com) organized the translation, welcome to forward, prohibited from reprinting The k-Nearest Neighbors algorithm (KNN) is based on a simple logic that is easy to understand and implement, making it a powerful tool you can use. By learning this tutorial, you will be able to implement a KNN algorithm from scratch in Python. … Read more
This series of tutorials serves as notes for the book “Hands-On Machine Learning.” First, let’s discuss the reasons for writing this series: First, the code in “Hands-On Machine Learning” is written in Python 2, and some of the code will throw errors when run on Python 3. This tutorial revises the code based on Python … Read more
Today is the seventh issue summarizing 16 major topics and 124 interview questions in machine learning: K-Nearest Neighbors (KNN) algorithm interview questions. The K-Nearest Neighbors (KNN) algorithm works by finding the K nearest neighbors of a sample and using the information from these K neighbors to make predictions. For classification tasks, the majority voting method … Read more
KNN Practical Application – Improving Matchmaking Effectiveness Introduction In simple terms, the KNN algorithm classifies data by measuring the distances between different feature values. The working principle is that there exists a sample dataset, namely the training dataset, and each sample in the dataset has a label, which indicates the correspondence between each data point … Read more
Deep learning has opened a new chapter in machine learning, and currently, there have been groundbreaking research advances in deep learning applications in image and speech. Deep learning has long been praised as an artificial intelligence algorithm similar to the structure of the human brain. So why has there been no substantial progress in the … Read more
After getting used to the operations of Word2Vec, today we will lift the lid and see what it’s really like inside. Word2Vec can transform words into vectors, which sounds quite magical, right? But once you understand the principle, you’ll find it’s just a little trick of assigning mathematical labels to words. Core Idea: Prediction Is … Read more
Submission by Machine Heart Author: Tang Zhengyang The author of this article, Tang Zhengyang, is the Market Manager at CreditX. He provides a clear introduction to the deep learning technology Word2vec and its applications in the field of financial risk control. In the current more inclusive market environment, the customer base and scope of new … Read more
Introduction Remember not long ago in the field of machine reading comprehension, where Microsoft and Alibaba surpassed humans on SQuAD with R-Net+ and SLQA respectively, and Baidu topped the MS MARCO leaderboard with V-Net while exceeding human performance on BLEU? These networks can be said to be increasingly complex, and it seems that the research … Read more
Click on the “AI Youdao” above to select the “Top” public account Heavyweight content delivered first-hand This article is reproduced from Big Data Digest, secondary reproduction is prohibited Translated by Zhang Qiuyue, Yihang, Gao Yan, Long Xincheng Embedding is one of the most fascinating ideas in machine learning. If you have ever used Siri, Google … Read more