California_House_Prices

Introduction

• This is a project that trains a model to predict the prices of houses in California using linear regression.
• This model uses real data collected during census which was conducted in the state.
• Real Estate has been one of the rising investments in the world and having such a model will help home buyers to be financially aware of price range as well as factors to settle on while buying a house.

Technologies Used

Python Libraries

• Pandas
• Numpy
• Matplotlib
• Seaborn
• Scikit-learn
• Python 3.6+
• Jupyter Notebook

• Other packages such as Basemap and pyplot are used alongside matplotlib.

Installation

• The packages and libraries can be installed in the Anaconda cmd using

  $ python -m pip install
  

or in the IDE directly mostly if you're using PyCharm.

Machine Learning Algorithm

• Linear Regression.