Category: Data Science
Notes from Data Science with Azure Talk @ TAP
I recently spoke at the Tampa Analytics Group, a Microsoft recognized Data Science group ran by Joe Blankenship on the topic of Data Science with Azure. The talk focused on Azure offerings, with a demo on how to write a map-redcuce job in Azure using C#. Following are the slides. Data science with Windows Azure - A…
"The Five Tribes of Machine Learning (And What You Can Learn from Each)," Pedro Domingos
Machine Learning for Big Data and Text Processing - Short Programs Testimonials
The five Tribes of Machine Learning, and other algorithmic tales
Pedro Domingos' The Master Algorithm - How the Quest for the Ultimate Learning Machine Will Remake Our World is an interesting and thought provoking book about the state of machine learning, data science, and artificial intelligence. Categorizing, classifying and clearly representing the ideas around any rapidly developing/evolving field is hard job. Machine learning with its…
On Explainability of Deep Neural Networks
During a discussion yesterday with software architect extraordinaire David Lazar regarding how everything old is new again, the topic of deep neural networks and its amazing success was brought up. Unless one is living under a rock for past five years, the advancements in artificial neural networks (ANN) has been quite significant and noteworthy. Since the…
Visualizing Decision Boundaries for Deep Learning
Decision boundary is the region of a problem space in which the output label of a classifier is ambiguous. In this concise yet informative article Dr. Takashi J Ozaki outlines decision boundaries for deep learning and other Machine Learning classifiers and emphasize on parameter tuning for Deep Learning. The source code for this article is on github, and he…