Linear Regression using Gradient Descent Algorithm Gradient descent is an optimization method used to find the minimum value of a function by iteratively updating the parameters of the function.

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

Understanding the Classification report in sklearn We often use the classification report to evaluate the quality of our predictions for classification algorithms.

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 number of clusters.

Understanding Support vector Machines using Python Support Vector machines (SVM) can be used for both classification as well as regression tasks but they are mostly used in classification applications.

Simple example of Polynomial regression using Python Previously I wrote an article explaining the underlying maths behind polynomial regression.

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 polynomial and c is a set of coefficients.

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 pizza from its diameter.