Practicing and Communicating Data Science with Jeff Stanton

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Practicing and Communicating Data Science with Jeff Stanton

FromData Skeptic

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37 minutes

Released:

Oct 24, 2014

Format:

Podcast episode

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Jeff Stanton joins me in this episode to discuss his book An Introduction to Data Science, and some of the unique challenges and issues faced by someone doing applied data science. A challenge to any data scientist is making sure they have a good input data set and apply any necessary data munging steps before their analysis. We cover some good advise for how to approach such problems.

Released:

Oct 24, 2014

Format:

Podcast episode

Titles in the series (100)

Data Skeptic is a data science podcast exploring machine learning, statistics, artificial intelligence, and other data topics through short tutorials and interviews with domain experts.

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[MINI] Experimental Design: This episode loosely explores the topic of Experimental Design including hypothesis testing, the importance of statistical tests, and an everyday and business example. by Data Skeptic
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The Secret and the Global Consciousness Project with Alex Boklin: 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... by Data Skeptic
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Data Science at ZestFinance with Marick Sinay: Marick Sinay from ZestFianance is our guest this weel. This episode explores how data science techniques are applied in the financial world, specifically in assessing credit worthiness. by Data Skeptic
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Mining the Social Web with Matthew Russell: This week's episode explores the possibilities of extracting novel insights from the many great social web APIs available. Matthew Russell's Mining the Social Web is a fantastic exploration of the tools and methods, and we explore a few... by Data Skeptic
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[MINI] The T-Test: The t-test is this week's mini-episode topic. The t-test is a statistical testing procedure used to determine if the mean of two datasets differs by a statistically significant amount. We discuss how a wine manufacturer might apply a t-test to... by Data Skeptic
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Easily Fooling Deep Neural Networks: My guest this week is Anh Nguyen, a PhD student at the University of Wyoming working in the Evolving AI lab. The episode discusses the paper Deep Neural Networks are Easily Fooled [pdf] by Anh Nguyen, Jason Yosinski, and Jeff Clune. It... by Data Skeptic
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Practicing and Communicating Data Science with Jeff Stanton: Jeff Stanton joins me in this episode to discuss his book An Introduction to Data Science, and some of the unique challenges and issues faced by someone doing applied data science. A challenge to any data scientist is making sure they have a... by Data Skeptic
37 min listen
[MINI] k-means clustering: The k-means clustering algorithm is an algorithm that computes a deterministic label for a given "k" number of clusters from an n-dimensional datset. This mini-episode explores how Yoshi, our lilac crowned amazon's biological processes might be... by Data Skeptic
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Discover this podcast and so much more

Practicing and Communicating Data Science with Jeff Stanton

Practicing and Communicating Data Science with Jeff Stanton

Description

Titles in the series (100)

More Episodes from Data Skeptic

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