This repository presents a machine learning project for predicting house prices, utilizing Python and Scikit-Learn. It encompasses data preprocessing, visualization, model training, and deployment via a Streamlit web app. The project includes data exploration, multiple model comparisons, and hyperparameter tuning.
From the README
🏠 House Price Prediction App 📌 Project Overview This project predicts house prices using Machine Learning. It includes complete data preprocessing, visualization, model training, and deployment using Streamlit. --- 🚀 Features • 📊 Data visualization and EDA (histograms, boxplots, correlation heatmap) • 🔄 End-to-end pipeline (preprocessing + model) • 🤖 Multiple model comparison • ⚙️ Hyperparameter tuning using GridSearchCV • 🌐 Interactive web app using Streamlit --- 🧠 Machine Learning Workflow 1️⃣ Data Analysis & Visualization • Distribution plots (histogram, KDE) • Boxplots for outlier detection • Correlation heatmap • Feature-target relationship analysis 2️⃣ Data...
Skills
- Jupyter Notebook
- Python
- data-analysis
- data-science
- machine-learning
- python
- streamlit
