What are Generative Models?

There are a lot of explanations elsewhere, here I’d like to share some example questions in an interview setting.

What are generative models?

Source: About Generative and Discriminative models

Here are some tips for readers’ reference:

Generative model is a class of models for unsupervised learning where given training data our goal is to try and generate new samples from the same distribution.

Let’s check out how Dr. Serena Yeung from Stanford explains it!

Check the explanation!

Happy practicing!

Thanks for reading my newsletter. You can follow me on Linkedin or Twitter @Angelina_Magr !

Note: There are different angles to answer an interview question. The author of this newsletter does not try to find a reference that answers a question exhaustively. Rather, the author would like to share some quick insights and help the readers to think, practice and do further research as necessary.

Source of video: Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 1.2 — Applications of Graph ML Convolutional Neural Networks for Visual Recognition (Spring 2017) Lecture 13 | Generative Models

Source of image: Medium blog. About Generative and Discriminative models