Linear regression is the problem where a model(line) is built with available data and then learnt model is used to predict target value for future data. This is the most basic type of statistical method used for predictive analysis. In other words, it can be understood as finding a relationship between target value and the attributes of input data.The best model is where we get minimum error between predicted and actual values.

## Networkx Tutorials – Learn network science with networkx

Networkx is a python library used to perform analysis over network data set. In this post, we will learn basics of network science using networkx.

## How to resolve VMware start error “Error while powering on : internal error in VMware”

If you experienced this error then you most probably will not be able to start you virtual machine. This post will provide solution to this error.

## How to generate data with Gaussian noise for linear regression problem

In this post, We will learn how to generate noisy data points where Gaussian error is added. For the demonstration purpose, we will use python’s matplotlib and numpy modules.

## Find out intersection points of two Gaussian distribution and calculate overlapping area

This post will provide tutorial on generating data from gaussian distribution, finding intersection data points and then computing overlapping area of two Gaussian distribution.