House-Price Prdiction

First ML practice project In this project I had taken Boston House dataset to make a ML model to predict prices Steps involved: We will load the data set from sklearn library which is in Dictionary format Convert the file into a dataframe Perform EDA operations to clean the dataset and draw the valuable insights We will use visualization techniques in this process Then after cleaning the data, by removing outliers, removing the skewness we will perform the ML To make ML model - we will split the data into train & test We will make the Machine Learn Then we will check the predicted values to the Original values for evaluation of the Model Then model can predict the price for new inputs given.