https://github.com/kedwar83/housing-prices-exploration

Using machine learning algorithms to explore housing prices
https://github.com/kedwar83/housing-prices-exploration

data-analysis data-science python school-project

Last synced: 13 days ago
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Using machine learning algorithms to explore housing prices

• Host: GitHub
• URL: https://github.com/kedwar83/housing-prices-exploration
• Owner: kedwar83
• Created: 2022-06-06T17:16:39.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2024-08-29T16:51:53.000Z (5 months ago)
• Last Synced: 2024-11-20T14:50:53.843Z (2 months ago)
• Topics: data-analysis, data-science, python, school-project
• Language: Jupyter Notebook
• Homepage:
• Size: 1.96 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# House Price Exploration Project

## Overview

This project explores house price prediction using various data analysis techniques and machine learning models. We'll go through several steps to clean our data, prepare it for analysis, and test different models to predict house prices.

## Main Steps

1. **Data Cleaning**

   - Remove missing or incorrect data

   - Prepare our dataset for analysis

2. **Feature Selection**

   - Choose which house features are most important for our prediction

   - Remove features that are too similar to each other

3. **Data Normalization**

   - Use log transformation to make our data more normal

   - This helps our models work better

4. **Model Testing**

   - Start with a simple Linear Regression model

   - Try more advanced techniques:

     - Principal Component Analysis (PCA)

     - Ridge Regression