Just as in many other countries, the housing market in the UK grew substantially during the coronavirus pandemic, fueled by robust demand and low borrowing costs. Nevertheless, high inflation and the increase in mortgage rates has led to house price growth slowing down. According to the forecast, 2024 is expected to see house prices decrease by three percent. Between 2024 and 2028, the average house price growth is projected at 2.7 percent. A contraction after a period of continuous growth In June 2022, the UK's house price index exceeded 150 index points, meaning that since 2015 which was the base year for the index, house prices had increased by 50 percent. In just two years, between 2020 and 2022, the index surged by 30 index points. As the market stood in December 2023, the average price for a home stood at approximately 284,691 British pounds. Rents are expected to continue to grow According to another forecast, the prime residential market is also expected to see rental prices grow in the next years. Growth is forecast to be stronger in 2024 and slow down in the period between 2025 and 2028. The rental market in London is expected to follow a similar trend, with Central London slightly outperforming Greater London.

Problem Statement 👉 Download the case studies here Investors and buyers in the real estate market faced challenges in accurately assessing property values and market trends. Traditional valuation methods were time-consuming and lacked precision, making it difficult to make informed investment decisions. A real estate firm sought a predictive analytics solution to provide accurate property price forecasts and market insights. Challenge Developing a real estate price prediction system involved… See the full description on the dataset page: https://huggingface.co/datasets/globosetechnology12/Real-Estate-Price-Prediction.

Overview: This dataset was collected and curated to support research on predicting real estate prices using machine learning algorithms, specifically Support Vector Regression (SVR) and Gradient Boosting Machine (GBM). The dataset includes comprehensive information on residential properties, enabling the development and evaluation of predictive models for accurate and transparent real estate appraisals.Data Source: The data was sourced from Department of Lands and Survey real estate listings.Features: The dataset contains the following key attributes for each property:Area (in square meters): The total living area of the property.Floor Number: The floor on which the property is located.Location: Geographic coordinates or city/region where the property is situated.Type of Apartment: The classification of the property, such as studio, one-bedroom, two-bedroom, etc.Number of Bathrooms: The total number of bathrooms in the property.Number of Bedrooms: The total number of bedrooms in the property.Property Age (in years): The number of years since the property was constructed.Property Condition: A categorical variable indicating the condition of the property (e.g., new, good, fair, needs renovation).Proximity to Amenities: The distance to nearby amenities such as schools, hospitals, shopping centers, and public transportation.Market Price (target variable): The actual sale price or listed price of the property.Data Preprocessing:Normalization: Numeric features such as area and proximity to amenities were normalized to ensure consistency and improve model performance.Categorical Encoding: Categorical features like property condition and type of apartment were encoded using one-hot encoding or label encoding, depending on the specific model requirements.Missing Values: Missing data points were handled using appropriate imputation techniques or by excluding records with significant missing information.Usage: This dataset was utilized to train and test machine learning models, aiming to predict the market price of residential properties based on the provided attributes. The models developed using this dataset demonstrated improved accuracy and transparency over traditional appraisal methods.Dataset Availability: The dataset is available for public use under the [CC BY 4.0]. Users are encouraged to cite the related publication when using the data in their research or applications.Citation: If you use this dataset in your research, please cite the following publication:[Real Estate Decision-Making: Precision in Price Prediction through Advanced Machine Learning Algorithms].

House prices in Spain are forecast to fall in 2024, after increasing by 1.2 percent in 2023. Nevertheless, prices are expected to pick up in 2025, with an increase of one percent. The Portuguese housing market, on the other hand, grew by 5.5 percent in 2023, but was forecast to contract in the next two years.

Context

This is a set of data created from imaginary data of house prices in an urban environment - Paris. I recommend using this dataset for educational purposes, for practice and to acquire the necessary knowledge. What I'm trying to do next is to create a classification dataset with same data from this dataset, I'll add a new column for class attribute ofc. Here is a classification dataset ---> classification dataset <---

Content

What's inside is more than just rows and columns. You can see house details listed as column names.

Description

All attributes are numeric variables and they are listed bellow:

• squareMeters
• numberOfRooms
• hasYard
• hasPool
• floors - number of floors
• cityCode - zip code
• cityPartRange - the higher the range, the more exclusive the neighbourhood is
• numPrevOwners - number of prevoious owners
• made - year
• isNewBuilt
• hasStormProtector
• basement - basement square meters
• attic - attic square meteres
• garage - garage size
• hasStorageRoom
• hasGuestRoom - number of guest rooms
• price - predicted value

Inspiration

Idea was to create dataset that is good for regression and that gives adequate results.

Housing Index in Saudi Arabia increased to 104.20 points in the fourth quarter of 2024 from 102.60 points in the third quarter of 2024. This dataset provides - Saudi Arabia Housing Index- actual values, historical data, forecast, chart, statistics, economic calendar and news.

According to the forecast, the North East and Wales are the regions in the United Kingdom estimated to see the highest overall growth in house prices over the five-year period between 2024 and 2028. Just behind are North West, Yorkshire & the Humber, and Scotland, which are forecast to see house prices increase by 20.2 percent over the five-year period. In London, house prices are expected to rise by 13.9 percent.

Dataset

This dataset was created by M Taimoor Akmal

Released under CC0: Public Domain

Contents

Single Family Home Prices in the United States increased to 398400 USD in February from 393400 USD in January of 2025. This dataset provides - United States Existing Single Family Home Prices- actual values, historical data, forecast, chart, statistics, economic calendar and news.

This is a real dataset of house prices sold in Seattle, Washing, USA between August and December 2022. The task is to predict the house price in this area based on several features, which are described below.

Feature Description beds Number of bedrooms in property baths Number of bathrooms in property. Note 0.5 corresponds to a half-bath which has a sink and toilet but no tub or shower size Total floor area of property size_units Units of the previous measurement lot_size Total area of the land where the property is located on. The lot belongs to the house owner lot_size_units Units of the previous measurement zip_code Zip code. This is a postal code used in the USA price Price the property was sold for (US dollars) Useful fact:

1 acre = 43560 sqft

Key information about House Prices Growth

• US house prices grew 5.2% YoY in Sep 2024, following an increase of 6.2% YoY in the previous quarter.
• YoY growth data is updated quarterly, available from Mar 1992 to Sep 2024, with an average growth rate of 5.5%.
• House price data reached an all-time high of 17.7% in Sep 2021 and a record low of -12.4% in Dec 2008.

According to the forecast, the UK regional prime property real estate market is to increase by almost 14 percent by 2028. In 2024, prime property prices are expected to fall by two percent. In the following four years, growth will recover.

Dataset

This dataset was created by fehu.zone

Released under Other (specified in description)

Contents

The Residential Real Estate Market Report is Segmented by Type (apartments and Condominiums and Landed Houses and Villas) and Geography (North America, Europe, Asia-Pacific, the Middle East and Africa, Latin America, and the Rest of the World). The Report Offers Market Sizes and Forecasts for the Residential Real Estate Market in USD for all the Above Segments.

Dataset

This dataset was created by Sohaib Anwaar

Contents

Housing Index in the United States increased to 436.50 points in January from 435.80 points in December of 2024. This dataset provides the latest reported value for - United States House Price Index MoM Change - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

House prices in Norway fell by 1.4 percent and, according to the forecast, are expected to continue to fall until 2024. In 2023, properties were forecast to experience a decline in prices of 12 percent. In 2025, growth is projected to recover, rising to five percent.

Housing Index in Portugal increased to 228.89 points in the third quarter of 2024 from 220.74 points in the second quarter of 2024. This dataset provides - Portugal House Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This repository contains the outcomes from the comparison made between three machine learning algorithms: Neural Network - MLP, Random Forest, and XGBoost. All algorithms were trained and went through the prediction phase based on a data set made of Brazilian house adversitments. paper.pdf - is the paper written, having the background around the studied topics and the outcomes themselves. output/raw/vivareal-announces-latest.tab - the data set.

The report covers Residential Real Estate Market in USA and is Segmented by Property Type (Apartments and Condominiums, Landed Houses and Villas). The report offers market size and forecasts for the residential real estate market in the United States in value (USD billion) for all the above segments.