Giter Site home page Giter Site logo

andrewrizk / predicting-house-prices Goto Github PK

View Code? Open in Web Editor NEW
0.0 1.0 0.0 255 KB

In this following practice, we will attempt to predict house prices in Iowa based on the House Prices Dataset on Kaggle: <https://www.kaggle.com/c/house-prices-advanced-regression-techniques>. The dataset presents different features of the houses that variably change the predictions. The data will require some work for cleaning and preprocessing to be ready for modeling. First, we will need to load the packages required for preprocessing and modeling phases. The steps of this practice will involve: 1 - Cleaning the data from null values using domain knowledge or practical judgements. 2 - Removing outliers from train data so they don't affect our predictions. 3 - Feature Engineering: this will involve transforming variables, creating new variables, and eliminating variables in favor of our predictions. 4 - Adjusting skewness for our numeric variables 5 - Using our transformed data with different practices and apply different evaluation models to predict the final price of each home

predicting-house-prices's Introduction

Predicting-House-Prices

In this following practice, we will attempt to predict house prices in Iowa based on the House Prices Dataset on Kaggle: <https://www.kaggle.com/c/house-prices-advanced-regression-techniques>.

The dataset presents different features of the houses that variably change the predictions. The data will require some work for cleaning and preprocessing to be ready for modeling. First, we will need to load the packages required for preprocessing and modeling phases.

The steps of this practice will involve: 1 - Cleaning the data from null values using domain knowledge or practical judgements. 2 - Removing outliers from train data so they don't affect our predictions. 3 - Feature Engineering: this will involve transforming variables, creating new variables, and eliminating variables in favor of our predictions. 4 - Adjusting skewness for our numeric variables 5 - Using our transformed data with different practices and apply different evaluation models to predict the final price of each home

predicting-house-prices's People

Contributors

andrewrizk avatar

Watchers

James Cloos avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.