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 saleprices for properties in Baltimore City based on Real Property Data
Exploration of kaggle House Price Data and building house price prediction models
DataScienceOverHood
买房客小程序, 专业买个好房子
This is a datathon project related to statistical testing and predictions.
Median House Value predictions, includes Reports explaining how was the inference made and r scripts for the same, also includes python code of the neural network applied
Project to predict the house price in Melbourne with R
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