A collection of data analysis and visualization projects designed to uncover insights from diverse datasets. These projects include analyses on COVID-19 trends, stock trading patterns, housing market prices, IoT data, and more, showcasing the power of data-driven storytelling.

A Python library enabling programmatic querying, filtering, and analysis of property listings on Daft.ie

A Machine Learning Project implemented from scratch which involves web scraping, data engineering, exploratory data analysis and machine learning to predict housing prices in New York Tri-State Area.

An API to allow developers to create applications using hyper local data on 27m homes, over 1m sale and rental listings, and 15 years of sold price data in the UK.

Python MLS and Real-Estate Data Scraper for the Realtor.ca Website

The "House Price Prediction" project focuses on predicting housing prices using machine learning techniques. By leveraging popular Python libraries such as NumPy, Pandas, Scikit-learn (sklearn), Matplotlib, Seaborn, and XGBoost, this project provides an end-to-end solution for accurate price estimation.

An example project that predicts house prices for a Kaggle competition using a Gradient Boosted Machine.

Unlocking Melbourne's housing market secrets! This project demystifies property prices by training a Random Forest model on key features. From a simple linear model to a fine-tuned powerhouse, it achieves an impressive 85% accuracy, turning data into predictive power.

Example project to predict housing pricing by using scikit, onnx and fastapi.

My machine learning capstone projects that predicts rental rates and property values in San Francisco using two datasets (Airbnb and SF Assessor data). I incorporate publicly available geospatial data to improve the accuracy of the models.

Building Toronto Housing dataset from scratch to predict real estate prices

Housing price prediction using Regularised linear regression

:house: Predict the selling price of a new home in Boston, Massachusetts area

No description available

Worked on Real Estate Price data analysis by scraping website from www.99acres.com to help the housing domain as well as estimate the sale value of various houses and open plots.

This is a regression problem to predict california housing prices.

Predict Housing Prices using Machine Learning.

Using rayshader to visualise 3D data with Hong Kong map

Predict housing prices in Portland, Oregon for selling or buying house

Web Crawler for scraping spanish housing prices (idealista)

This project applies basic machine learning concepts on Ames Housing dataset to predict the selling price of a new home.

I have built a Model using Random Forest Regressor of California Housing Prices Dataset to predict the price of the Houses in California.

Predictive Analytics project on housing price analysis using machine learning models.

This notebook explores the housing dataset from Kaggle to predict Sales Prices of housing using advanced regression techniques such as feature engineering and gradient boosting.

Web scrap on divar website (Tehran) to generate a dataset on housing price in Tehran.

ML model trained on data from Bayut.com to predict housing prices in Dubai

Deploying a containerized machine learning app, which estimates housing prices, using Docker and Kubernetes (locally).

This repository includes a file uploaded as part of a project on [insert topic, e.g., data analysis, web development, automation, etc.]. The primary objective of this file is to demonstrate or support work related to [brief purpose, e.g., exploring housing price trends, building a login system, automating data entry, etc.].

Housing prices competition based on entrylevel and intermediate ML courses

Development of hedonic models of rents and sales prices for housing