Metis Data Science Bootcamp : Project Directory
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Updated
May 16, 2018 - HTML
Metis Data Science Bootcamp : Project Directory
this is from kaggle competition on finding out the house price according to the given training and testing set given.
A high performance repo for kaggle house price prediction.
Yangon apartment price dataset range between 20 Million Kyat(သိန်း ၂၀၀) and 50 Million Kyat (သိန်း ၅၀၀)
Project - 1- Multiple linear regression problem using House Price Data. “LetsUpgrade-FS Data Science-[Suwarna Baraskar]”.
Modelling houses prices in Ames Iowa with advanced regression techniques like Random Forest, GBR, XGBoost or LASSO-RIDGE.
Within this undertaking, a range of regression methodologies shall be explored in order to address a compelling conundrum.
Linear Regression, Logistic Regression, ML Pipeline
This repository uses a simple linear regression to predict house prices in US $ based upon areas in sq ft.
Predicting Property Prices in Pakistan
This project aims to analyze the Bengaluru House Data using Python. The dataset is loaded from a CSV file named "Bengaluru_House_Data.csv" and is analyzed to gain insights into the housing market in Bengaluru.
Predict sales prices and practice feature engineering, RFs, and gradient boosting
My project (XGBoost.ipynb) using the gradient boosting algorithm for evaluating real estate objects in St. Peresburg on the example of the XGBoost library based on collected dataset (deals_dataset.csv). This dataset is colleted from https://portal.rosreestr.ru/wps/portal/p/is/cc_informSections/ais_mrn during 2016-2017 years for training a model …
Train a neural network to predict the prices of houses in Ames, Iowa.
Simple regression to predict the house sales price in King County, USA
Austrian housing market information deployed as Dash web app.
A Flask app that scrapes, aggregates, and plots rentals in Canada.
The ultimate goal of the project is to build a prediction engine capable of predicting district's median housing price
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