House Sales Price Prediction Competition - ImmoSense 🏡💰

This project aims to analyze data about houses and predict the sales price. 📊

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🔎 Project Overview

When buyers describe their dream home, they often focus on aspects like the number of bedrooms or the presence of a garden. 🌳🏠 However, many hidden factors, such as basement height or proximity to a railway 🚂, also influence the final sale price. Through a vigorous analysis, we explain how these hidden factors impact the price. 🔍💡

👨🏽‍💻🧐 EDA + Model Selection

See the EDA file for detailed exploratory data analysis and model selection insights. 📈🤓

📁 File System

    |_📂data
    | |_____📄data_description.txt
    | |_____📄submission.csv
    | |_____📄test.csv
    | |_____📄train.csv
    |
    |_📂insight_plot
    | |_____(*🗺️ plots.pnd....)
    |
    |_📂notebook
    | |________📄keyFactor.txt
    | |________📄main.ipynb
    |
    |_⚙️ app.py
    |_📄README.md
    |_📄requirements.txt

⚠️ (solution is stored in data/submission.csv) ⚠️

🤔 How to Use ?

• Install anaconda and activate the conda software using conda activate
• then run these following commands

git clone https://github.com/superMass14/immoSense.git
cd immoSense
conda create --name immoSense --file requirements.txt
conda activate immoSense
code .

you can check our dashborad here

Acknowledgments 🎉

• Organizator 🤝
  Z01_dkr_AI_community

• Authors

@Licensed by SMM team🔐