Predicting Amsterdam house / real estate prices using Ordinary Least Squares-, XGBoost-, KNN-, Lasso-, Ridge-, Polynomial-, Random Forest-, and Neural Network MLP Regression (via scikit-learn)

Implementation of Regression Models on Navigation with IMUs.

Source for the book Fun Computer Science Projects in Python.

asthma-rates.com - predict asthma rates after changes in social policy - Data Science Capstone Project

Boston house price prediction.

A k-nearest neighbors algorithm is implemented in Python from scratch to perform a classification or regression analysis.

This repository contains projects related to KNN algorithm using R, Python

Engineer's Thesis

Machine Learning engine generates predictions given any dataset using regression

Scripts for the paper "Application of machine learning regression models to inverse eigenvalue problems". Authors Nikolaos Pallikarakis and Andreas Ntargaras. Correspondence at npall@central.ntua.gr.

Implementations of Machine Learning models, Regularizers, Optimizers and different Cost functions.

Makine Öğrenmesi ile İkinci El Otomobil Fiyatlarının Tahmin Edilmesi / PredictingSecond Hand Car Prices with Machine Learning

Pong with Pygame and k-NN Prediction Algorithm (KNeighborsRegressor) for Opponent

The kNN algorithm is one of the most famous machine learning (ML) algorithms. It's generally used for classification, especially when you have more than two categories.

stock price prediction with K Nearest Neighbors Regressor

Book recommender api written in flask framework

Real time chess video tracker

Making cancer classification with knn module (Kaggle Expression)

K-NN Algorithm with various similarity measures

Imagery pipeline utilizing neural networks