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...