big data

In episode twelve we talk with Andrew Ng, Chief Scientist at Baidu, we’re introduced to random features for large-scale kernel machines, and we take a listener question about the size of computing power in machine learning. 

The Economic Impact of Machine Learning and Using The Kernel Trick To Dig In To Big Data

In episode fifteen we talk with Max Welling, of the University of Amsterdam and University of California Irvine. We talk with him about his work with extremely large data and big business and machine learning. We take a listener question about the relationship between machine learning and artificial intelligence. Plus, we get an introduction to change point detection. 

Really Really Big Data and Machine Learning in Business

Artist: Squim
Album: Synaptic Seepage
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2017
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06 - Big Data Deep Dump

In this episode of the Data Show, I spoke with Jeremy Stanley, VP of data science at Instacart, a popular grocery delivery service that is expanding rapidly. As Stanley describes it, Instacart operates a four-sided marketplace comprised of retail stores, products within the stores, shoppers assigned to the stores, and customers who order from Instacart. The objective is to get fresh groceries from popular retailers delivered to customers in a timely fashion. Instacart’s goals land them in the center of the many opportunities and challenges involved in building high-impact data products.

Data Science and Deep Learning in Retail

Alex thinks dropout is cool. He's still not quite sure what batch normalization is. Regarding ImageNet competition, Apurva, along with offering tips to staying motivated to learning  says that instead of creating "new" models, people are only doing ensembling now to get a marginal edge over everyone else. Edderic announces revamping his PC workstation for deep learning (bye-bye Amazon!)

Episode 007 - Lesson 3 - Part 2 (Practical Deep Learning for Coders)

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06 - Big Data Deep Dump

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