Data Skeptic (general)

Yusan Lin shares her research on using data science to explore the fashion industry in this episode. She has applied techniques from data mining, natural language processing, and social network analysis to explore who are the innovators in the fashion world and how their influence effects other designers.

If you found this episode interesting and would like to read more, Yusan's papers Text-Generated Fashion Influence Model: An Empirical Study on and The Hidden Influence Network in the Fashion Industry are worth reading.

Direct download: yusan_lin.mp3
Category:general -- posted at: 12:01am PDT

[MINI] PageRank

PageRank is the algorithm most famous for being one of the original innovations that made Google stand out as a search engine. It was defined in the classic paper The Anatomy of a Large-Scale Hypertextual Web Search Engine by Sergey Brin and Larry Page. While this algorithm clearly impacted web searching, it has also been useful in a variety of other applications. This episode presents a high level description of this algorithm and how it might apply when trying to establish who writes the most influencial academic papers.

Direct download: pagerank.mp3
Category:general -- posted at: 12:01am PDT


How do people think rationally about small probability events?

What is the optimal statistical process by which one can update their beliefs in light of new evidence?

This episode of Data Skeptic explores questions like this as Kyle consults a cast of previous guests and experts to try and answer the question "What is the probability, however small, that Bigfoot is real?"

Direct download: Data_Skeptic_-_Crypto.mp3
Category:general -- posted at: 2:34am PDT

A recent episode of the Skeptics Guide to the Universe included a slight rant by Dr. Novella and the rouges about a shortcoming in operating systems.  This episode explores why such a (seemingly obvious) flaw might make sense from an engineering perspective, and how data science might be the solution.

In this solo episode, Kyle proposes the concept of "annoyance mining" - the idea that with proper logging and enough feedback, data scientists could be provided the right dataset from which they can detect flaws and annoyances in software and other systems and automatically detect potential bugs, flaws, and improvements which could make those systems better.

As system complexity grows, it seems that an abstraction like this might be required in order to keep maintaining an effective development cycle.  This episode is a bit of a soap box for Kyle as he explores why and how we might track an appropriate amount of data to be able to make better software and systems more suited for the users.

Direct download: annoyance_mining.mp3
Category:general -- posted at: 11:18pm PDT

This episode contains converage of the 2015 Data Fest hosted at UCLA.  Data Fest is an analysis competition that gives teams of students 48 hours to explore a new dataset and present novel findings.  This year, data from was provided, and students competed in three categories: best recommendation, best use of external data, and best visualization.

Direct download: Data_Fest_2015.mp3
Category:general -- posted at: 11:55pm PDT

Nicole Goebel joins us this week to share her experiences in oceanography studying phytoplankton and other aspects of the ocean and how data plays a role in that science.


We also discuss Thinkful where Nicole and I are both mentors for the Introduction to Data Science course.

Last but not least, check out Nicole's blog Data Science Girl and the videos Kyle mentioned on her Youtube channel featuring one on the diversity of phytoplankton and how that changes in time and space.

Direct download: Oceanography_and_Data_Science.mp3
Category:general -- posted at: 12:06am PDT

I'm joined this week by Alex Boklin to explore the topic of magical thinking especially in the context of Rhonda Byrne's "The Secret", and the similarities it bears to The Global Consciousness Project (GCP). The GCP puts forward the hypothesis that random number generators elicit statistically significant changes as a result of major world events.

Direct download: The_Secret_and_the_Global_Consciousness_Project.mp3
Category:general -- posted at: 12:05am PDT

This miniepisode discusses the technique called Cross Validation - a process by which one randomly divides up a dataset into numerous small partitions. Next, (typically) one is held out, and the rest are used to train some model. The hold out set can then be used to validate how good the model does at describing/predicting new data.

Direct download: MINI_Cross_Validation.mp3
Category:general -- posted at: 7:51am PDT

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 ws found? 

Direct download: Streetlight_Outage_and_Crime_Rate_Analysis_with_Zach_Seeskin.mp3
Category:general -- posted at: 6:00am PDT

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.


Direct download: Data_Skeptic_Podcast_-_Big_Data_Tools.mp3
Category:general -- posted at: 6:00am PDT