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.
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< 1 day ago
If one machine learning model is good, are two models better? In a lot of cases, the answer is yes. If you build many ok models, and then bring them all together and use them in combination to make your final predictions, you've just created an ensemble model. It feels a little bit like cheating, like you just got something for nothing, but the results don't like: algorithms like Random Forests and Gradient Boosting Trees (two types of ensemble algorithms) are some of the strongest out-of-the-box algorithms for classic supervised classification problems. What makes a Random Forest random, and what does it mean to gradient boost a tree? Have a listen and find out.
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 4 out of
I Love Udacity, I hope you always updated this podcast
Date published: 2015-04-25