datascience
🚀 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
My New Acheivement
Excited to share that I have officially earned the IBM Data Science Foundations - Level 2 (V2) Badge! Following up on Level 1, I’ve completed all three specialized courses to achieve Level 2 certification from IBM: 1️⃣ Data Science 101 – Fundamental concepts, real-world applications, and business impact. 2️⃣ Data Science Methodology – Structured problem-solving frameworks from business understanding to deployment. 3️⃣ Data Science Hands-on with Open Source Tools – Practical experience working with open-source environments like Jupyter Notebooks, RStudio, and IBM Watson Studio. This journey has strengthened my hands-on appreciation for data science workflows, model deployment principles, and collaborative open-source tooling. A big thank you to IBM and Cognitive Class / IBM Skills Network for providing such structured learning paths! Onward to the next milestone in Data Science & Machine Learning! Credential Verification: https://www.credly.com/badges/e75c5648-b0e5-460e-a3cc-87743ff5793d