Metis Data Science Bootcamp : Project Directory
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Updated
May 16, 2018 - HTML
Metis Data Science Bootcamp : Project Directory
Project - 1- Multiple linear regression problem using House Price Data. “LetsUpgrade-FS Data Science-[Suwarna Baraskar]”.
Linear Regression, Logistic Regression, ML Pipeline
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.
Within this undertaking, a range of regression methodologies shall be explored in order to address a compelling conundrum.
End to end ML project implementation
Predict saleprices for properties in Baltimore City based on Real Property Data
Project to predict the house price in Melbourne with R
In this notebook, I have done data analysis on house price prediction problem
Predicting prices of houses using regression
Predicting the new house prices in bengaluru
A Data Science approach to predict house sales from given dataset. All steps from CRISP-DM Framework are accounted for and Linear Regression is used for modelling.
In this project we will work on developing an end to end machine learning project using linear regression. We will be doing extensive data visualization, we will perform data feature engineering, we will also see how we can select features based on the correlation of the features.
A price prediction model and price valuation tool for properties in Dubai, United Arab Emirates
Predicting House Price using machine learning techniques provided by the Turicreate library.
A minimal machine learning application using PySpark
House price prediction using linear regression
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