The Predicting House Prices in Bengaluru Machine Learning Project aims to build a predictive model that can accurately predict the prices of houses in Bengaluru based on various factors such as location, size, number of rooms, and other related features. The project will leverage various machine learning algorithms, including regression, decision trees, random forests, and gradient boosting, to build the predictive model.
The project will involve several key steps, including data cleaning and preprocessing, feature engineering, model selection, and model training and evaluation. The dataset will be sourced from various real estate websites and will contain several features such as location, size, number of rooms, age of the property, and other related features.
The dataset will be cleaned and preprocessed to remove any missing values, outliers, or irrelevant features. The dataset will be split into training and testing sets to train and evaluate the model’s performance. Feature engineering will be performed to extract relevant features from the dataset.
The model will be trained using the selected features and different machine learning algorithms. The best-performing algorithm will be selected based on the evaluation metrics, such as Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and R-squared score. The model’s performance will be evaluated on the testing dataset, and the accuracy of the predictions will be measured using evaluation metrics.
The project will also involve visualization techniques to explore the dataset and gain insights into the relationship between different features and house prices. The visualization techniques will include scatter plots, histograms, and box plots, among others.
The final output of the project will be a web-based application that can take in data on various house features such as location, size, number of rooms, and other related features and provide a prediction of the house prices in Bengaluru. The Predicting House Prices in Bengaluru Machine Learning Project is aimed at providing valuable insights into the factors that contribute to house prices in Bengaluru and providing an accurate prediction of the house prices based on various features. The project can be useful for both buyers and sellers in making informed decisions about real estate transactions.
