You want to be the best real estate agent out there. In order to compete with other agents in your area, you decide to use machine learning. You are going to use various statistical analysis tools to build the best model to predict the value of a given house. Your task is to find the best price your client can sell their house at. The best guess from a model is one that best generalizes the data.
The objective of the project is to perform data visulalization techniques to understand the insight of the data. Machine learning often requires to get the understanding of data and its insights. This project aims at applying various Python tools to get a visual understanding of the data and clean it to make it ready to apply machine learning algorithms to it.
The notebook includes all the markdowns which explain the process.
The dataset is taken from kaggle. The file contains housing data from USA.
- Fork it!
- Create your feature branch: git checkout -b my-new-feature
- Commit your changes: git commit -am 'Add some feature'
- Push to the branch: git push origin my-new-feature
- Submit a pull request :D
This repo is maintained by @GOD-OF-FIRE (mailto:kushagra357@gmail.com)