oasisinfobyte

🚀 Built a House Price Prediction Model using Python & Machine Learning

I built a **House Price Prediction** project as part of my **Data Science Internship at Oasis Infobyte**. ## 📌 Project Overview The goal of this project is to predict house prices based on different property-related features using **Machine Learning**. ## 🔄 Project Workflow **Dataset → Data Cleaning → EDA → Feature Selection → Model Training → Evaluation → Price Prediction** ### 🧹 Data Preparation * Loaded and explored the dataset using **Pandas** * Handled missing and inconsistent data * Prepared the dataset for machine learning ### 📊 Exploratory Data Analysis * Analyzed relationships between different features * Created visualizations to identify patterns and trends * Studied factors affecting house prices ### 🤖 Machine Learning * Selected relevant features * Split the dataset into training and testing sets * Trained a regression model * Evaluated the model using appropriate performance metrics ### 🎯 Prediction The trained model takes property-related features as input and generates an estimated **house price**. ## 🛠️ Tech Stack `Python` `Pandas` `NumPy` `Matplotlib` `Scikit-learn` `Jupyter Notebook` ## 💡 Key Learning This project gave me hands-on experience with the complete machine learning workflow — from **data preprocessing and visualization to model training, evaluation, and prediction**. ## 🔗 GitHub Repository 👉https://github.com/pallavisagar07/OIBSIP/tree/ec73e94f0a9d2ea3a3fe3e65c1676d8c0af17219/DataAnalytics-L2-House-Price-Prediction-Linear-Regression #Python #MachineLearning #DataScience #DataAnalytics #ScikitLearn #OasisInfobyte #ProjectShowcase