About This Show
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.
Most Recent Episode
Things You Learn When Building Models for Big Data
6 days ago
As more and more data gets collected seemingly every day, and data scientists use that data for modeling, the technical limits associated with machine learning on big datasets keep getting pushed back. This week is a first-hand case study in using scikit-learn (a popular python machine learning library) on multi-terabyte datasets, which is something that Katie does a lot for her day job at Civis Analytics. There are a lot of considerations for doing something like this--cloud computing, artful use of parallelization, considerations of model complexity, and the computational demands of training vs. prediction, to name just a few.
Rated 4 out of
Podcasting with obstacles
She is lovely, humble, and knows her stuff. He is an annoying dumb who interrupts her every 20 seconds with nonsenses, wild guesses and long rants about topics he doesn't know, putting it hard for her to make her point. It's worth hearing because of her, but gee, you have to have a lot of patience because of him.
Date published: 2016-10-26
Rated 5 out of
James From JAMSO
A super show that is enough for the newbies and also informed for the world of machine learning and AI.
Great insights and discussions that are easy to refer, apply and understand. - Nice job
Date published: 2017-02-24
Rated 4 out of
I Love Udacity, I hope you always updated this podcast
Date published: 2015-04-25