feat: Add Real Estate Price Prediction project files and documentation

[Naveen-Boddepalli]

Issue Title : Real Estate Price Prediction #684

• Info about the related issue (Aim of the project) : Build a robust ML + Deep Learning pipeline to predict real estate prices in Bengaluru using the Bengaluru House Price dataset from Kaggle. Models include Linear Regression, Lasso, Random Forest, XGBoost, MLP, and Wide & Deep Network, evaluated using R², MAE, and RMSE.
• Name: Naveen Boddepalli
• GitHub ID: Naveen-Boddepalli
• Email ID: 1234naveenboddepalli@gmail.com
• Identify yourself: GSSoC 2026 Participant

Closes: #684

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Describe the add-ons or changes you've made 📃

Added a complete Real-Estate-Price-Prediction/ project folder containing:

• Data Preprocessing — handled missing values in bath, balcony, society; parsed size to BHK count; handled total_sqft ranges; engineered price_per_sqft; removed outliers per location using std deviation; grouped rare locations; applied One-Hot Encoding.
• EDA — price distribution, correlation heatmap, top locations by median price, sqft vs price scatter plot.
• ML Models — Linear Regression (baseline), Lasso Regression, Random Forest, XGBoost with GridSearchCV tuning.
• Deep Learning Models — MLP (BatchNorm + Dropout + ReLU) and Wide & Deep Network (PyTorch), both with learning rate scheduler and early stopping.
• Results — MLP and Wide & Deep outperformed all ML models (R² ~0.65, RMSE ~75 Lakhs). Full comparison bar charts included.
• Saved model — best model saved as .pkl via joblib.
• Documentation — README.md with approach, results table, model comparison, and conclusions. Dataset/README.md with column descriptions and download instructions.

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Type of change ☑️

• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Code style update (formatting, local variables)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• This change requires a documentation update

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How Has This Been Tested? ⚙️

• Notebook executed end-to-end on Google Colab (Python 3.12) using the Bengaluru House Price dataset.
• All 6 models trained and evaluated — metrics logged in the results table.
• Visualizations generated and saved to Images/ folder.
• Preprocessing pipeline verified on 13,000+ rows after cleaning and outlier removal.
• Model comparison confirmed MLP and Wide & Deep as best performers across R², MAE, and RMSE.

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Checklist: ☑️

• My code follows the guidelines of this project.
• I have performed a self-review of my own code.
• I have commented my code, particularly wherever it was hard to understand.
• I have made corresponding changes to the documentation.
• My changes generate no new warnings.
• I have added things that prove my fix is effective or that my feature works.
• Any dependent changes have been merged and published in downstream modules.

[github-actions]

Our team will soon review your PR. Thanks @Naveen-Boddepalli :)

[abhisheks008]

1. Project folder name should be Real Estate Price Prediction, NO underscores & hyphens.
2. README files seem blank & information are missing. Please fix it.
3. Jupyter Notebook file seems unreachable and the file contents are not able to load. Please check.

@Naveen-Boddepalli

[Naveen-Boddepalli]

okay i will create a new folder with that name then

[Naveen-Boddepalli]

Hi @abhisheks008, the notebook can be viewed on Google Colab here:
https://colab.research.google.com/drive/1sCo3sGl2wCyczfPcnlTZSVj8QaL2OJSb?usp=sharing
GitHub's built-in .ipynb renderer has a known issue with this file. The notebook runs successfully end-to-end and all outputs, visualizations, and model results are visible via the Colab link above.

• you can check with other notebooks also in your repo, all of them faces the same issue

[Naveen-Boddepalli]

Hi @abhisheks008, the notebook can be viewed here:
Colab: https://colab.research.google.com/drive/1sCo3sGl2wCyczfPcnlTZSVj8QaL2OJSb?usp=sharing
HTML Preview: https://htmlpreview.github.io/?https://raw.githubusercontent.com/Naveen-Boddepalli/DL-Simplified/main/Real%20Estate%20Price%20Prediction/Model/Real_Estate_Price_Prediction.html

[Naveen-Boddepalli]

hi @abhisheks008,
it's been two weeks from opening this pr, can please review this pr when you are free.
thank you.