Linear Digressions

Linear Digressions

Linear Digressions is a podcast about machine learning and data science. Machine learning is being used to solve a ton of interesting problems, and to accomplish goals that were out of reach even a few short years ago. 896520

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Episoder(309)

Stealing a PIN with signal processing and machine learning

Stealing a PIN with signal processing and machine learning

Want another reason to be paranoid when using the free coffee shop wifi? Allow us to introduce WindTalker, a system that cleverly combines a dose of signal processing with a dash of machine learning ...

21 Nov 201616min

Neural Net Cryptography

Neural Net Cryptography

Cryptography used to be the domain of information theorists and spies. There's a new player now: neural networks. Given the task of communicating securely, neural networks are inventing new encrypti...

14 Nov 201616min

Deep Blue

Deep Blue

In 1997, Deep Blue was the IBM algorithm/computer that did what no one, at the time, though possible: it beat the world's best chess player. It turns out, though, that one of the most important moves...

7 Nov 201620min

Organizing Google's Datasets

Organizing Google's Datasets

If you're a data scientist, there's a good chance you're used to working with a lot of data. But there's a lot of data, and then there's Google-scale amounts of data. Keeping all that data organized...

31 Okt 201615min

Fighting Cancer with Data Science: Followup

Fighting Cancer with Data Science: Followup

A few months ago, Katie started on a project for the Vice President's Cancer Moonshot surrounding how data can be used to better fight cancer. The project is all wrapped up now, so we wanted to tell ...

24 Okt 201625min

The 19-year-old determining the US election

The 19-year-old determining the US election

Sick of the presidential election yet? We are too, but there's still almost a month to go, so let's just embrace it together. This week, we'll talk about one of the presidential polls, which has bee...

17 Okt 201612min

How to Steal a Model

How to Steal a Model

What does it mean to steal a model? It means someone (the thief, presumably) can re-create the predictions of the model without having access to the algorithm itself, or the training data. Sound far...

9 Okt 201613min

Regularization

Regularization

Lots of data is usually seen as a good thing. And it is a good thing--except when it's not. In a lot of fields, a problem arises when you have many, many features, especially if there's a somewhat s...

3 Okt 201617min

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