Data Science Videos

In this video, we discuss how to design statistical regression and machine learning models to predict the number of COVID-19 (coronavirus) cases in countries across the world.

In this video, we discuss our recent research where we collect and study Twitter communications to understand the socio-economic impact of COVID-19 in the United States during the early days of the pandemic

Support Vector Mahines

In this video, we introduce Support Vector Machines or SVMs. 

In this video, we explain kernels, one of the essential components of Support Vector Machines (SVMs).

In this video, we explain Support Vector Machines (SVMs) using a simple example.

Decision Trees

In this video,we present an example of using Decision Tree Scitkit Learn on the Iris dataset.

In this video, we discuss practical considerations in designing a decision tree model. We discuss how to overcome overfitting in decision trees, three ways to prune the tree, and how to handle missing attributes and continuous values.

In this video, we explain decision tree information gain using an example.

Neural Networks

In this video, we explain how to update weights in a neural network using the backpropagation algorithm (Case I).

In the video, we explain how to update weights using backpropagation algorithm in neural networks (Case II).

In this video, we learn how to compute the error Gradient for the Sigmoid unit.

Probability Basics

In this video, we discuss Bernoulli and Binomial random variables. We also study an example balls and bins problem that can be modeled using a binomial random variable.

In this video, we provide an overview of Poisson distribution. The video also show the relationship between binomial and Poisson distributions.

In this video, we explain the balls and bins and the coupon collector’s problem.