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)

The Care and Feeding of Data Scientists: Growing Careers

The Care and Feeding of Data Scientists: Growing Careers

In the third and final installment of a conversation with Michelangelo D’Agostino, VP of Data Science and Engineering at Shoprunner, about growing and mentoring data scientists on your team. Some of o...

11 Nov 201925min

The Care and Feeding of Data Scientists: Recruiting and Hiring Data Scientists

The Care and Feeding of Data Scientists: Recruiting and Hiring Data Scientists

This week’s episode is the second in a three-part interview series with Michelangelo D’Agostino, VP of Data Science at Shoprunner. This discussion centers on building a team, which means recruiting, i...

4 Nov 201920min

The Care and Feeding of Data Scientists: Becoming a Data Science Manager

The Care and Feeding of Data Scientists: Becoming a Data Science Manager

Data science management isn’t easy, and many data scientists are finding themselves learning on the job how to manage data science teams as they get promoted into more formal leadership roles. O’Reill...

28 Okt 201924min

Procella: YouTube's super-system for analytics data storage

Procella: YouTube's super-system for analytics data storage

If you’re trying to manage a project that serves up analytics data for a few very distinct uses, you’d be wise to consider having custom solutions for each use case that are optimized for the needs an...

21 Okt 201929min

Kalman Runners

Kalman Runners

The Kalman Filter is an algorithm for taking noisy measurements of dynamic systems and using them to get a better idea of the underlying dynamics than you could get from a simple extrapolation. If you...

13 Okt 201915min

What's *really* so hard about feature engineering?

What's *really* so hard about feature engineering?

Feature engineering is ubiquitous but gets surprisingly difficult surprisingly fast. What could be so complicated about just keeping track of what data you have, and how you made it? A lot, as it turn...

6 Okt 201921min

Data storage for analytics: stars and snowflakes

Data storage for analytics: stars and snowflakes

If you’re a data scientist or data engineer thinking about how to store data for analytics uses, one of the early choices you’ll have to make (or live with, if someone else made it) is how to lay out ...

30 Sep 201915min

Data storage: transactions vs. analytics

Data storage: transactions vs. analytics

Data scientists and software engineers both work with databases, but they use them for different purposes. So if you’re a data scientist thinking about the best way to store and access data for your a...

23 Sep 201916min

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