Analyze the Boston house Price Data & Give Prediction

Welcome to Boston Massachusetts in the 1970s! Imagine you're working for a real estate development company. Your company wants to value any residential project before they start. You are tasked with building a model that can provide a price estimate based on a home's characteristics like:

• The number of rooms

• The distance to employment centres

• How rich or poor the area is

• How many students there are per teacher in local schools etc

What I've learned:

✅ Analysed and explored the Boston house price data

✅ Splited data for training and testing

✅ Ran a Multivariable Regression

✅ Evaluated model's coefficients and residuals

✅ Used data transformation to improve your model performance

✅ Used your model to estimate a property price

How to Run:

OR

Download and add the Notebook to Google Drive

As usual, download the repo, extract it & Add the .ipynb file into your Google Drive and open it as a Google Colaboratory notebook.

Add the Data to the Notebook

The .zip file also includes a .csv file. This is the data for the project. Add this your notebook.