The point of deep learning is using a deep graph, like a neural network with a lot of layers, not the amount of data.

However, picking millions of parameters with small amounts of data is unlikely to work well.

It seems, at first blush, like using a very complex model to fit a very small amount of data is a recipe for some serious overfitting.

I would agree. Its kind of amazing that it indeed it does seem to work better than simpler models.

yeah that's what i was trying to say. Saying you can construct a deep graph using small data feels like "I'm gonna become a millionaire in ten years, only by operating this single lemonade stand"