Real Estate Price Prediction

• Gathered relevant data, Cleaned and prepared the collected data by handling missing values, removing outliers.
• Created new features and transformed existing ones to capture important information that can influence real estate prices.
• Explore and visualize the data to gain insights into its distribution, correlations, and patterns.
• Chose apropriate machine learning algorithm or predictive model for the task.
• Trained the selected model on the training data, optimizing its parameters to make accurate predictions.