Aurélie Pols draws a broad philosophical picture of the data ecosystem and then hones in on the right to data portability.
A glimpse into what lies ahead for response automation, model compliance, and repeatable experiments.
Alysa Hutnik discusses the Fair Credit Reporting Act, the Equal Credit Opportunity Act, the Gramm-Leach Bliley Act, and the FTC’s focus on FinTech.
Regardless of country or culture, any solid data science plan needs to address veracity, storage, analysis, and use.
The O’Reilly Data Show Podcast: Leo Meyerovich on building large-scale, interactive applications that enable visual investigations.
Using machine learning to understand and leverage text.
The ability to appeal may be the most important part of a fair system, and it's one that isn't often discussed in data circles.
Exploring many small regions of a graph with low latency using specialized graph and multi-model databases.
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The adventures in deep learning and cheap hardware continue!
June Andrews talks about simple, cost-effective algorithmic computing at scale.
Working with uncertainty in real-world data.
How to build a class of RL agents using a TensorFlow notebook.
Decoding simple regex features to match complex text patterns.
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“Data is having an impact on business models and profitability. It’s hard to find a non-trivial application that doesn’t use data in a significant manner.”— Ben Lorica, Director of Content Strategy for Data at O'Reilly Media