An Executive Primer to Deep Learning

Circa 1997, the reigning world chess champion Garry Kasparov was against an unknown opponent. The opponent was formidable. Garry was not playing a human. He was playing the game with IBM’s behemoth supercomputer, Deep Blue. Garry had beaten the opponent in the last few games. However, the game played on 11th May 1997 game was […]

TOP TRENDS IN ARTIFICIAL INTELLIGENCE IN 2018

According to Gartner’s hype cycle of emerging technologies, 2017; Deep Learning and Machine Learning have reached the peak of inflated expectations. Artificial General Intelligence (AGI) and Deep Reinforcement Learning are in the phase of innovation trigger. I have published this article on Analytics Insight that looks into the top trends in Artificial Intelligence in 2018. Happy […]

Data Science Simplified Part 11: Logistic Regression

In the last blog post of this series, we discussed classifiers. The categories of classifiers and how they are evaluated were discussed. We have also discussed regression models in depth. In this post, we dwell a little deeper in how regression models can be used for classification tasks. Logistic Regression is a widely used regression […]

Data Science Simplified Part 6: Model Selection Methods

In the last article of this series, we had discussed multivariate linear regression model. Fernando creates a model that estimates the price of the car based on five input parameters. Fernando indeed has a better model. Yet, he wanted to select the best set of variables for input. This article will elaborate on model selection […]