This post is continuation to the previous posts on Data Science process. We will try to predict housing prices based on some training dataset. I am using Ames housing dataset and based on my previous posts on the process this will be in continuation to them. In my previous posts, Read more…
In my previous post i briefly discussed about different techniques of handling missing data for building Machine Learning model. Below is Python script for treating missing data in Ames dataset. (Download the dataset from here) As usual open Jupyter notebook and import our libraries to start import pandas as pd Read more…
Missing data is one of the most common / frequent occurrence in real world Data Science. This can happen in data collection phase in different ways. For Example, people may not answer all questions during a survey or the data might be constructed from multiple sources which might not have Read more…