/PredictingCaliforniaHousingPrices

Predicting the Housing prices in California dataset

Primary LanguageJupyter Notebook

Predicting the California Housing Prices

Dataset from statLib repository

Main steps followed in the project are:

1)Looking at the big picture

2)Get the Data

3)Discover and visualize the data to gain insights

4)Prepare the data for ML algorithms

5)Select a model and train it

6)Fine-tuning the model

7)Present your solution

8)Launch, monitor, and mainitain the system

Technologies and Tool Used :

Programming Language : Python

Source ditribution : Anaconda

Libraries: NumPy, Pandas, SciPy

packages to install : SciKit learn, Pandas, NumPy, SciPy

Usage

Just run jupyter notebook in terminal and you can visit the notebook in your web browser.

Install jupyter from here

Results :

The median income is the number one predictor of the housing prices