Determining the housing prices of California properties for new sellers and also for buyers to estimate the profitability of the deal.

The aim of this project to see to do the prediction of the weather using the different types of machine learning model.

A model was built to predict the total insurance claim amount payable by the insurance company using machine learning techniques such as regression in python.

Bike Sharing Demand Prediction By Supervised Machine Learning Algorithms Implementation On Seoul Bike Sharing Dataset

Machine learning project to predict NYC property prices.

Machine Learning Examples for Beginners

KOR: 개인 프로젝트. 머신러닝을 통해 테니스 선수 랭킹 예측. ENG: A personal project. Predicts rankings of tennis players using linear regression, decision tree regressor and random forest.

Predicting using Decision Tree Regressor and Random Forest Regressor

This repository contains a comprehensive analysis and predictive modeling project for the National Iranian Gas Company. The project aims to explore gas consumption data, identify patterns and anomalies, and predict future consumption trends using various statistical and machine learning models.

🏡House Price Prediction, Artificial Intelligence course, University of Tehran

Third Assignment in 'Practical topics in Machine Learning' course by Dr. Kfir Bar at Bar-Ilan University

Predicting breast cancer survival using machine learning models

This repository contains implementations of popular machine learning algorithms including Support Vector Machine (SVM), Decision Tree, and Naive Bayes. Each algorithm is implemented separately, providing clear and concise examples of their usage for classification tasks.

Exploring the impact of socioeconomic indicators on hardship in Chicago neighborhoods using machine learning. Leveraging Linear Regression, Decision Tree, random forest, and Agglomerative Clustering, the project identifies key factors—unemployment, lack of a high school diploma, and poverty—highlighting disparities in the dataset from 2008-2012

Predicting house prices can help determine the selling price of a house in a particular region and can help people find the right time to buy a home.

A decision tree implementation from scratch using Python, NumPy and pandas for four cases of real/discrete features/output.

Implemented a Decision Tree Regressor, a Gradient Boosting Regressor, and a Hierarchical Clustering Algorithm.

Determining the Sales of Audi Cars across whole Europe by comparing the specifications as well as the price of some bestselling Models.

Using a dataset provided by Airbnb, analysis and predictions will be made to understand what effects the total price of an Airbnb