Fueling innovative software
July 15-18, 2019
Portland, OR

Learn neural networks with Go—not math

Ellen Korbes (garden.io)
4:15pm4:55pm Wednesday, July 17, 2019
Secondary topics:  AI Enhanced

Who is this presentation for?

  • Software developers




It’s common for even the most amazing programmers to not have the first clue about math. That makes learning neural networks particularly inaccessible, as an integral part of explaining it relies on mathematical formulas. Ah, the formulas…with all their lines and curves and ancient symbols; they’re just as unintelligible as they are beautiful.

What’s a better way for us to learn it instead? With a language we all speak: code.

Ellen Körbes dives into every component required to write a neural network from scratch, like network structure, activation functions, forward propagation, gradient descent, and backpropagation. But you look at them as programmers: we define what we’re trying to achieve, then write an implementation for it. You do that with no specialized libraries like TensorFlow and PyTorch—only Go code. So if you ever wanted to really understand how a neural network works, but thought it to be out of your reach because of the math, this is for you. Code, not math. Algorithms, not logarithms.

Prerequisite knowledge

  • Experience writing code
  • Familiarity with Go (useful but not necessary)

What you'll learn

  • Learn all the fundamental parts of a neural network in a manner you can easily comprehend and follow
Photo of Ellen Korbes

Ellen Korbes


Ellen Körbes works with developer relations at Garden. They code, write, speak, teach Go, make videos, and dabble with Kubernetes. A native of Brazil, they’re deeply involved with diversity and inclusiveness in tech.

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