ref : https://towardsdatascience.com/no-machine-learning-is-not-just-glorified-statistics-26d3952234e3
Regression Over 100 Million Variables — No Problem?
Let me also point out the difference between deep nets and traditional statistical models by their scale. Deep neural networks are huge. The VGG-16 ConvNet architecture, for example, has approximately 138 million parameters. How do you think your average academic advisor would respond to a student wanting to perform a multiple regression of over 100 million variables? The idea is ludicrous. That’s because training VGG-16 is not multiple regression — it’s machine learning.