K-fold cross validation The greatest headache for any machine learning engineer is the problem of overfitting. Continue Reading →
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. Continue Reading →
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. Continue Reading →
Understanding the Classification report in sklearn We often use a classification report to check the quality of classification algorithm predictions. Continue Reading →
K-Means on Iris Dataset Read my previous post to understand how K-Means algorithm works. Continue Reading →
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. Continue Reading →
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. Continue Reading →
Simple example of Polynomial regression using Python Previously I wrote an article explaining the underlying maths behind polynomial regression. Continue Reading →
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. Continue Reading →
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. Continue Reading →
