Learn how to implement the K-Nearest Neighbors (KNN) algorithm from scratch in Python! This tutorial covers the theory, coding process, and practical examples to help you understand how KNN works ...

A data-driven inventory optimization project solving stock inefficiencies using SQL, Power BI & forecasting logic on 100K+ records. Includes KPIs, dashboards & strategic insights — under Consulting & ...

Learn the Adagrad optimization algorithm, how it works, and how to implement it from scratch in Python for machine learning models. #Adagrad #Optimization #Python Trump administration looking to sell ...

ABSTRACT: The objective of this work is to determine the true owner of a land—public or private—in the region of Kumasi (Ghana). For this purpose, we applied different machine learning methods to the ...

Abstract: The density peak anomaly detection algorithm based on KNN, one of the most frequently utilized classical algorithms, is widely applied in communication fields, such as network fault ...

This project demonstrates how to implement the K-Nearest Neighbors (KNN) algorithm for classification on a customer dataset. The program iterates through different values of k (number of neighbors) ...

Abstract: Machine learning is about prediction on unseen data or testing data and a set of algorithms are required to perform task on machine learning. There are three types of machine learning are ...