Deep Learning with Yacine on MSN

Build k-nearest neighbors from scratch in Python – step by step tutorial

Learn how to implement the K-Nearest Neighbors (KNN) algorithm from scratch in Python! This tutorial covers the theory, ...
IEEE

Determining The Parameter K of K-Nearest Neighbors (KNN) using Random Grid Search

Abstract: The study aims to optimize the classification of reception of training participants using the K-Nearest Neighbors (KNN) algorithm by finding the optimal value for the K parameter through a ...
IEEE

Parameter Identification of Permanent Magnet Synchronous Motor Based on CGCRAO Algorithm

Abstract: In response to the challenge of easily falling into local optima and slow identification speed in the parameter identification of permanent magnet synchronous motors (PMSMs), this paper ...
GitHub

Hansen Solubility Parameters in Python.

HSPiPy is a Python library designed for calculating and visualizing Hansen Solubility Parameters (HSP). It provides machine-learning–friendly estimators, convenient data import, and plotting tools for ...