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…
Outlier treatment and Featuring Engineering would be the next steps in continuation to Missing Data Treatment. Outliers Definition: An outlier is an observation that lies an abnormal distance from other values in a random sample from a population. It is an observation that deviates from overall pattern on a sample. Outliers can 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…
I covered about Python basics in my previous post and now lets move on to understand how to do exploratory data analysis using Python. As mentioned in my earlier post, the power of Python comes from its libraries. Below I would like to give a brief introduction to the most Read more…
Python is an open source multipurpose programming language used for many different applications. There is a huge community backing which made this open source language very popular. The power of its capabilities comes from the number of libraries it supports which is only growing through the community. The main downside Read more…
Continuation of Part-2 Mean: The average or central value Mean Absolute Error: As the name says it is Mean of Absolute Error. Absolute Error is the difference between forecasted value and actual value. So MAE is the mean of those values. Example: If a weighing scale shows 10KG whereas the Read more…
Continuation from Part-1 Part-2: Decision trees: These are type of machine learning algorithms which is very good tool to choose between several courses of actions. It is choosing by expected outcomes from the given data. They are shown as inverted trees with root at the top. Example: We can build a Read more…
There are some commonly used terms in the learning path of Data Science. I have made my list of few such terms and try to briefly explain them in as simply terms as possible. Do not take them as definitions but instead perceive them as a basic understanding of the Read more…
What is Data Science? Data Science becoming widely popular in the last few years hasn’t managed to find a place in English dictionary yet for its definition. However Oxford defines Data as “Facts and statistics collected together for reference or analysis” and Science as “The intellectual and practical activity encompassing Read more…