Our guest this week is Hamilton physics professor Kate Jones-Smith who joins us to discuss the evidence for the claim that drip paintings of Jackson Pollock contain fractal patterns. This hypothesis originates in a paper by Taylor, Micolich, and Jonas titled Fractal analysis of Pollock's drip paintings which appeared in Nature.  Kate and co-author Harsh Mathur wrote a paper titled Revisiting Pollock's Drip Paintings which also appeared in Nature. A full text PDF can be found here, but lacks the helpful figures which can be found here, although two images are blurred behind a paywall.  Their paper was covered in the New York Times as well as in USA Today (albeit with with a much more delightful headline: Never mind the Pollock's [sic]).  While discussing the intersection of science and art, the conversation also touched briefly on a few other intersting topics. For example, Penrose Tiles appearing in islamic art (pre-dating Roger Penrose's investigation of the interesting properties of these tiling processes), Quasicrystal designs in art, Automated brushstroke analysis of the works of Vincent van Gogh, and attempts to authenticate a possible work of Leonardo Da Vinci of uncertain provenance. Last but not least, the conversation touches on the particularly compellingHockney-Falco Thesis which is also covered in David Hockney's book Secret Knowledge.  For those interested in reading some of Kate's other publications, many Katherine Jones-Smith articles can be found at the given link, all of which have downloadable PDFs.

Our topic for this week is "noise" as in signal vs. noise.  This is not a signal processing discussions, but rather a brief introduction to how the work noise is used to describe how much information in a dataset is useless (as opposed to useful). Also, Kyle announces having recently had the pleasure of appearing as a guest on The Conspiracy Skeptic Podcast to discussion The Bible Code.  Please check out this other fine program for this and it's many other great episodes.

Our guest this week is Susan Gerbic. Susan is a skeptical activist involved in many activities, the one we focus on most in this episode is Guerrilla Skepticism on Wikipedia, an organization working to improve the content and citations of Wikipedia.  During the episode, Kyle recommended Susan's talk a The Amazing Meeting 9 which can be found here.  Some noteworthy topics mentioned during the podcast were Neil deGrasse Tyson's endorsement of the Penny for NASA project. As well as the Web of Trust and Rebutr browser plug ins, as well as how following the Skeptic Action project on Twitter provides recommendations of sites to visit and rate as you see fit via these tools.  For her benevolent reference, Susan suggested The Odds Must Be Crazy, a fun website that explores the statistical likelihoods of seemingly unlikely situations. For all else, Susan and her various activities can be found via SusanGerbic.com.

Discover Ant Colony Optimization, a search and optimization technique inspired by ants' behavior. Learn how it can be applied to find the best route in cities like San Francisco. Explore the concept of local optima, multidimensional optimization, and strategies to optimize a restaurant. Understand how ants use pheromone trails to find food and how this behavior inspires computer algorithms for search problems.

Our guest this week is Shahid Shah. Shahid is CEO at Netspective, and writes three blogs: Health Care Guy, Shahid Shah, and HitSphere - the Healthcare IT Supersite. During the program, Kyle recommended a talk from the 2014 MIT Sloan CIO Symposium entitled Transforming "Digital Silos" to "Digital Care Enterprise" which was hosted by our guest Shahid Shah. In addition to his work in Healthcare IT, he also the chairperson for Open Source Electronic Health Record Alliance, an non-profit organization that, amongst other activities, is hosting an upcoming conference. The 3rd annual OSEHRA Open Source Summit: Global Collaboration in Healthcare IT , which will be taking place September 3-5, 2014 in Washington DC. For our benevolent recommendation, Shahid suggested listeners may benefit from taking the time to read books on leadership for the insights they provide. For our self-serving recommendation, Shahid recommended listeners check out his company Netspective , if you are working with a company looking for help getting started building software utilizing next generation technologies.

This podcast mini-episode discusses the technique of Cross Validation, which involves splitting a dataset into small partitions, training a model, and validating its predictive power. The hosts explore the importance of models, good fit, and the process of training. They highlight the significance of cross-validation in data science to avoid overfitting and improve predictive power, using examples such as predicting sales data and training a jazz music classifier. Finally, they explain the concept of cross-validation in machine learning and its usefulness for limited or new data.

This episode features a discussion with statistics PhD student Zach Seeskin about a project he was involved in as part of the Eric and Wendy Schmidt Data Science for Social Good Summer Fellowship.  The project involved exploring the relationship (if any) between streetlight outages and crime in the City of Chicago.  We discuss how the data was accessed via the City of Chicago data portal, how the analysis was done, and what correlations were discovered in the data.  Won't you listen and hear what was found? 

This episode loosely explores the topic of Experimental Design including hypothesis testing, the importance of statistical tests, and an everyday and business example.

In this week's episode, we discuss applied solutions to big data problem with big data engineer Jay Shankar.  The episode explores approaches and design philosophy to solving real world big data business problems, and the exploration of the wide array of tools available.  

This podcast discusses Bayesian Updating, exploring how beliefs change based on new evidence. It uses examples of searching for keys, discovering a pomegranate, and using bags of fruits to understand belief updates. The concept of Bayesian updating and probability is explored, along with the use of Bayes' theorem.