Neural Networks With Pound Cakes and a Little Math

Author(s): Renu Gehring

Originally published on Towards AI.

Gentle introduction to neural networks
Photo by charlesdeluvio on Unsplash

My family loves pound cakes, and I enjoy baking them, especially this time of the year. Did you know that the pound cake is aptly named because it uses a pound of butter, flour, sugar, and eggs? A dozen eggs. Six whole eggs and six egg yolks give the pound cake its rich color and its dense yet melt-in-your-mouth silky texture.

What might happen if you experimented with different combinations of whole eggs and yolks? Ms. Baker, an imaginary friend of mine, did just that. An infinitely curious person, Ms. Baker is also interested in neural networks. This post describes how Ms. Baker learned about neural networks through reading and experimentation.

Ms. Baker conducts a number of experiments, using her children to test her cakes. The kids are discerning; they either gobble up with their mom’s creations or refuse to eat them altogether. Ms. Baker’s quality measure is her products’ destination: tummies or compost bin. Cake Quality is 0/1 (compost bin/tummies).

Table created by author

Ms. Baker discovered that she could go two steps in either direction of the optimal 6 eggs and 6 yolks. Her kids will eat the cake, but any further deviations, like 3 whole eggs and… Read the full blog for free on Medium.

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Published via Towards AI