Ollama: Local Large Model Running Guide

Ollama: Local Large Model Running Guide

The author of this article is a front-end developer at 360 Qiwutuan. Introduction to Ollama Ollama is an open-source framework developed in Go that can run large models locally. Official website: https://ollama.com/ GitHub repository: https://github.com/ollama/ollama Installing Ollama Download and Install Ollama Choose the appropriate installation package based on your operating system type from the Ollama … Read more

Understanding KNN Algorithm Through a Matchmaking Story

Understanding KNN Algorithm Through a Matchmaking Story

This article is reprinted from the public account Xinkou Dushuo KNN is a fundamental data classification algorithm in machine learning. Here, I will explain its utility through a story. Let’s start with a joke. During a matchmaking event, a beautiful girl asked the young man: Do you have a three-bedroom apartment? The young man: No. … Read more

Getting Started with KNN in C Language for Machine Learning

Getting Started with KNN in C Language for Machine Learning

I originally planned to work overtime for two days over the weekend, but suddenly other matters came up and were canceled. By the way, I looked at CSDN and saw an article introducing KNN. Since I am also working in the field of machine learning, I naturally need to understand some of this part. What … Read more

Introduction to KNN Algorithm in Machine Learning

Introduction to KNN Algorithm in Machine Learning

CodingGo Technical Community A Free Programming Learning Platform Algorithm Introduction KNN (K-Nearest Neighbors) is a simple machine learning algorithm that does not require learning any parameters and can be used for both classification and regression problems. The intuitive explanation of this algorithm is ‘Birds of a feather flock together.’ When a new sample is input, … Read more

Summary of K-Nearest Neighbors (KNN) Algorithm Principles

Summary of K-Nearest Neighbors (KNN) Algorithm Principles

Table of Contents 1. Principles of KNN Algorithm 2. Three Elements of KNN Algorithm 3. Brute Force Implementation of KNN Algorithm 4. KD-Tree Implementation of KNN Algorithm 5. Imbalance in Training Samples for KNN Algorithm 6. Advantages and Disadvantages of the Algorithm 1. Principles of KNN Algorithm The KNN algorithm selects the k nearest training … Read more

Implementing KNN Algorithm in Python from Scratch

Implementing KNN Algorithm in Python from Scratch

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

The Misconceptions About Word2Vec: A Programmer’s Insight

The Misconceptions About Word2Vec: A Programmer's Insight

Li Zi from Ao Fei Si Quantum Bit | WeChat Official Account QbitAI Word2Vec is a language tool open-sourced by Google in 2013. A two-layer network can turn words into vectors, which is crucial in the NLP field and the foundation for many functionalities. However, now a programmer named bollu (short for Pineapple) loudly tells … Read more

Knowledge Graphs for E-Commerce: Understanding User Needs

Knowledge Graphs for E-Commerce: Understanding User Needs

AliMe Guide: This article explains the construction of knowledge graphs in the e-commerce domain from the perspective of demand analysis and systematic building, detailing the entire conceptual system formed during the process. It also emphasizes the significant efforts made by algorithm, engineering, product, operation, and outsourcing teams to gradually refine the platform architecture and review … Read more

Comprehensive Explanation of XGBoost Algorithm

Comprehensive Explanation of XGBoost Algorithm

This article is a part of Chapter 10 of the book “Introduction to Machine Learning Basics” (by Huang Haiguang). XGBoost Algorithm XGBoost is a machine learning algorithm based on the Gradient Boosting Decision Tree (GBDT) invented in February 2014 by PhD student Chen Tianqi from the University of Washington. This algorithm not only has excellent … Read more

Detailed Derivation of XGBoost Explained

Detailed Derivation of XGBoost Explained

– What is the basis for tree node splitting in XGBoost? – How is the weight of tree nodes calculated? – What improvements has XGBoost made to prevent overfitting? Those reading this article are likely familiar with XGBoost. Indeed, XGBoost is not only a powerful tool in major data science competitions but is also widely … Read more