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(308)

Racism, the criminal justice system, and data science

Racism, the criminal justice system, and data science

As protests sweep across the United States in the wake of the killing of George Floyd by a Minneapolis police officer, we take a moment to dig into one of the ways that data science perpetuates and am...

7 Jun 202031min

An interstitial word from Ben

An interstitial word from Ben

A message from Ben around algorithmic bias, and how our models are sometimes reflections of ourselves.

5 Jun 20205min

Convolutional Neural Networks

Convolutional Neural Networks

This is a re-release of an episode that originally aired on April 1, 2018 If you've done image recognition or computer vision tasks with a neural network, you've probably used a convolutional neural ...

31 Mai 202021min

Stein's Paradox

Stein's Paradox

This is a re-release of an episode that was originally released on February 26, 2017. When you're estimating something about some object that's a member of a larger group of similar objects (say, th...

24 Mai 202027min

Protecting Individual-Level Census Data with Differential Privacy

Protecting Individual-Level Census Data with Differential Privacy

The power of finely-grained, individual-level data comes with a drawback: it compromises the privacy of potentially anyone and everyone in the dataset. Even for de-identified datasets, there can be wa...

18 Mai 202021min

Causal Trees

Causal Trees

What do you get when you combine the causal inference needs of econometrics with the data-driven methodology of machine learning? Usually these two don’t go well together (deriving causal conclusions ...

11 Mai 202015min

The Grammar Of Graphics

The Grammar Of Graphics

You may not realize it consciously, but beautiful visualizations have rules. The rules are often implict and manifest themselves as expectations about how the data is summarized, presented, and annota...

4 Mai 202035min

Gaussian Processes

Gaussian Processes

It’s pretty common to fit a function to a dataset when you’re a data scientist. But in many cases, it’s not clear what kind of function might be most appropriate—linear? quadratic? sinusoidal? some co...

27 Apr 202020min

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