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(328)

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

The Cold Start Problem

The Cold Start Problem

You might sometimes find that it's hard to get started doing something, but once you're going, it gets easier. Turns out machine learning algorithms, and especially recommendation engines, feel the s...

26 Sep 201615min

Open Source Software for Data Science

Open Source Software for Data Science

If you work in tech, software or data science, there's an excellent chance you use tools that are built upon open source software. This is software that's built and distributed not for a profit, but ...

19 Sep 201620min

Scikit + Optimization = Scikit-Optimize

Scikit + Optimization = Scikit-Optimize

We're excited to welcome a guest, Tim Head, who is one of the maintainers of the scikit-optimize package. With all the talk about optimization lately, it felt appropriate to get in a few words with s...

12 Sep 201615min

Two Cultures: Machine Learning and Statistics

Two Cultures: Machine Learning and Statistics

It's a funny thing to realize, but data science modeling is usually about either explainability, interpretation and understanding, or it's about predictive accuracy. But usually not both--optimizing ...

5 Sep 201617min

Optimization Solutions

Optimization Solutions

You've got an optimization problem to solve, and a less-than-forever amount of time in which to solve it. What do? Use a heuristic optimization algorithm, like a hill climber or simulated annealing-...

29 Aug 201620min

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