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Regression analysis; Ridge and Lasso
What is regression analysis? In the terms of statistical modeling, regression analysis refers to a technique of determining the relationship between variables. We consider two types of variables, dependent and independent. More specifically speaking, regression analysis deals with the behavoiur of a dependent variable w.r.t to an indepedent variable. Behaviour...
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K-Means clustering algorithm
K-means clustering is an unsupervised machine learning technique to cluster data sets into specified number of clusters. It can be used in both classification and regression problems. This article is broadly divided into three subparts. Firstly, the problem statement, then the algorithm to solve it and analysis of different approaches,...
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My first Blockchain Hackathon
I with two other amazing people participated in the I_Hack hackathon organized by E-cell, IIT Bombay in Jan 2019. The hackathon was of blockchain track and the participants were free to choose their own idea and work on it. For me, blockchain was a complete new track, because it is...
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The Perceptron Learning Algorithm
What is a Perceptron? The Perceptron is a parameterised function which takes a real-valued vector as input and gives a Boolean output. It was introduced by Rosenblatt over half a century ago. The output of the perceptron is given by thresholding a linear function of the input vector. The parameters...
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Hosting a blog on github pages
Github gives a free option to host webpages of your own with an extension of github.io. Developers can have a portfolio website or a demo of a project, or even a blog page. This post is regarding how I hosted this blog on github pages. Follow the steps to get...
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Ensemble learning, Bagging and Boosting
What is ensemble learning? Ensemble learning is a machine learning technique, where multiple hypotheses combined to give the final output. For example, for classifying red and green balls, instead of using one perceptron, we may use multiple weak perceptrons and combine their output. Let’s say we have 5 perceptrons and...