Predicting Tokyo House Prices: Data Cleaning, EDA, and Machine Learning

In this project, In this project, I’m going to use a dataset that is related to real estate in Tokyo in Japan to make a price estimator for houses. During this project, first I clean and preprocess the dataset. After that, I run exploratory data analysis (EDA) to know the data much better and do some statistical techniques. In the next step, I analyze the correlation between variables. Finally, I build the regression machine learning model and tune it with the hyper-parameter method

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Predicting Tokyo House Prices: Data Cleaning, EDA, and Machine Learning

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