House Price Prediction using Machine Learning & Python | End-to-End Project | Mayars Coding School

In this video, we build a complete House Price Prediction model from scratch using Python and Machine Learning. Whether you're a beginner or looking to add a solid project to your portfolio, this step-by-step guide covers everything from data cleaning to model evaluation.

📍 What we cover in this video:
Data Exploration (EDA): Visualizing trends and correlations in housing data.
Data Preprocessing: Handling missing values, outliers, and categorical encoding.
Feature Engineering: Selecting the most impactful features (sqft, bedrooms, location).
Model Building: Implementing algorithms like Linear Regression, Random Forest, or XGBoost.
Performance Metrics: Evaluating our model using R-squared, MAE, and RMSE.

🛠 Tools & Technologies:
Python (Pandas, NumPy)
Scikit-Learn (Machine Learning)
Matplotlib & Seaborn (Visualization)
Jupyter Notebook / VS Code

Видео House Price Prediction using Machine Learning & Python | End-to-End Project | Mayars Coding School канала MCS Services