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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Are machine learning engineers the new data scientists?

Are machine learning engineers the new data scientists?

For many data scientists, maintaining models and workflows in production is both a huge part of their job and not something they necessarily trained for if their background is more in statistics or ma...

4 Maalis 201920min

Interview with Alex Radovic, particle physicist turned machine learning researcher

Interview with Alex Radovic, particle physicist turned machine learning researcher

You’d be hard-pressed to find a field with bigger, richer, and more scientifically valuable data than particle physics. Years before “data scientist” was even a term, particle physicists were inventin...

25 Helmi 201935min

K Nearest Neighbors

K Nearest Neighbors

K Nearest Neighbors is an algorithm with secrets. On one hand, the algorithm itself is as straightforward as possible: find the labeled points nearest the point that you need to predict, and make a pr...

17 Helmi 201916min

Not every deep learning paper is great. Is that a problem?

Not every deep learning paper is great. Is that a problem?

Deep learning is a field that’s growing quickly. That’s good! There are lots of new deep learning papers put out every day. That’s good too… right? What if not every paper out there is particularly go...

11 Helmi 201917min

The Assumptions of Ordinary Least Squares

The Assumptions of Ordinary Least Squares

Ordinary least squares (OLS) is often used synonymously with linear regression. If you’re a data scientist, machine learner, or statistician, you bump into it daily. If you haven’t had the opportunity...

3 Helmi 201925min

Quantile Regression

Quantile Regression

Linear regression is a great tool if you want to make predictions about the mean value that an outcome will have given certain values for the inputs. But what if you want to predict the median? Or the...

28 Tammi 201921min

Heterogeneous Treatment Effects

Heterogeneous Treatment Effects

When data scientists use a linear regression to look for causal relationships between a treatment and an outcome, what they’re usually finding is the so-called average treatment effect. In other words...

20 Tammi 201917min

Pre-training language models for natural language processing problems

Pre-training language models for natural language processing problems

When you build a model for natural language processing (NLP), such as a recurrent neural network, it helps a ton if you’re not starting from zero. In other words, if you can draw upon other datasets f...

14 Tammi 201927min