The greatest headache for any machine learning engineer is the problem of overfitting. The model we trained works...

## Linear Regression using Gradient Descent Algorithm

Gradient descent is an optimization method used to find the minimum value of a function by iteratively updating...

## Mathematics of Principal component analysis

Principal component analysis is a method used to reduce the number of dimensions in a dataset without losing...

## Understanding the Classification report in sklearn

We often use a classification report to check the quality of classification algorithm predictions. A sample report is...

## K-Means on Iris Dataset

Read my previous post to understand how K-Means algorithm works. In this post I will try to run...

## Mathematics behind K-Mean Clustering algorithm

K-Means is one of the simplest unsupervised clustering algorithm which is used to cluster our data into K...

## Understanding Support vector Machines using Python

Support Vector machines (SVM) can be used for both classification as well as regression tasks but they are...

## Simple example of Polynomial regression using Python

Previously I wrote an article explaining the underlying maths behind polynomial regression. In this post I will use...

## Maths behind Polynomial regression

Polynomial regression is a process of finding a polynomial function that takes the form f( x ) = c0 + c1 x + c2 x2 ⋯ cn xn where n is the degree of the...

## Multiple Linear Regression with Python on Framingham Heart Study data

Previously we built a simple linear regression model using a single explanatory variable to predict the price of...