Hi. My name is Suyash Shivaji Phatak and this is my project which I have done during the udemy course of Machine Learning named Machine Learning A to Z. The tools and libraries really helped me to complete this project succesfully. I have collected data from kaggle for my project. From this project, I have used different models for prediction of the house price. The names of the models that I used are Multiple Linear Regression Model, Polynomial Linear Regression Model, Decision Tree Regression Model, Random Forest Regression Model, Support Vector Regression Model. According the 'R squared score', Support Vector Model has greatest value among other models. Hence, we will be predicting using the suppor vector model.
Clone this repo to your local machine using https://github.com/suyashphatak23/Real-Estate-Price-Predictor
- Clone the repository or open the jupyter notebook using Google Colab or Anaconda IDE or Local Jupyter Notebook.
- Make sure the dataset set should be in the same location where the notebook is.
- Then run the code blocks sequentially, you will get the output.
Note: While running the notebook locally, you should have all the python libraries such as scikit-learn, pandas, matplotlib and numpy.
