This is a series on Data Science and Machine Learning applied to a House Prices dataset from the Kaggle competition House Prices: Advanced Regression Techniques.
In this series we begin with the EDA (Exploratory Data Analysis) of the data, we create a script to clean the data, then we use the cleaned data to create a Machine Learning Model, and finally we use the Machine Learning model to implement a prediction API:
- Exploratory Data Analysis – House Prices – Part 1
- Exploratory Data Analysis – House Prices – Part 2
- Data Science Project: Data Cleaning Script – House Prices DataSet
- Data Science Project: Machine Learning Model – House Prices Dataset
- Data Science Project: House Prices Dataset - API
You can download the complete code in the Github Repository with clear instructions to execute this end-to-end project.
>>>You can also watch how to run this project on Youtube<<<