Data Skeptic

Recently, we've seen opinion polls come under some skepticism.  But is that skepticism truly justified?  The recent Brexit referendum and US 2016 Presidential Election are examples where some claims the polls "got it wrong".  This episode explores this idea.

Direct download: polling.mp3
Category:general -- posted at: 8:00am PST

No reliable, complete database cataloging home sales data at a transaction level is available for the average person to access. To a data scientist interesting in studying this data, our hands are complete tied. Opportunities like testing sociological theories, exploring economic impacts, study market forces, or simply research the value of an investment when buying a home are all blocked by the lack of easy access to this dataset. OpenHouse seeks to correct that by centralizing and standardizing all publicly available home sales transactional data. In this episode, we discuss the achievements of OpenHouse to date, and what plans exist for the future.

Check out the OpenHouse gallery.

I also encourage everyone to check out the project Zareen mentioned which was her Harry Potter word2vec webapp and Joy's project doing data visualization on Jawbone data.

Guests

Thanks again to @iamzareenf, @blueplastic, and @joytafty for coming on the show. Thanks to the numerous other volunteers who have helped with the project as well!

Announcements and details

Sponsor

Thanks to our sponsor for this episode Periscope Data. The blog post demoing their maps option is on our blog titled Periscope Data Maps.

Periscope Data

To start a free trial of their dashboarding too, visit http://periscopedata.com/skeptics

Kyle recently did a youtube video exploring the Data Skeptic podcast download numbers using Periscope Data. Check it out at https://youtu.be/aglpJrMp0M4.

Supplemental music is Lee Rosevere's Let's Start at the Beginning.

 

Direct download: openhouse.mp3
Category:general -- posted at: 8:30am PST

There's more than one type of computer processor. The central processing unit (CPU) is typically what one means when they say "processor". GPUs were introduced to be highly optimized for doing floating point computations in parallel. These types of operations were very useful for high end video games, but as it turns out, those same processors are extremely useful for machine learning. In this mini-episode we discuss why.

Direct download: gpu-cpu.mp3
Category:general -- posted at: 8:00am PST

Backpropagation is a common algorithm for training a neural network.  It works by computing the gradient of each weight with respect to the overall error, and using stochastic gradient descent to iteratively fine tune the weights of the network.  In this episode, we compare this concept to finding a location on a map, marble maze games, and golf.

Direct download: backpropagation.mp3
Category:general -- posted at: 8:00am PST

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