Learn Neural Networks With Go—Not Math! (Interview)
summary
Builds a working neural network from scratch in Go with plain Go implementation and no libraries, no magic, showing readable code for forward pass and backprop so developers see every calculation instead of trusting TensorFlow or PyTorch. Compares that simple approach to heavier options like TensorFlow PyTorch and the fast.ai course, argues core intuition beats early math, and gives a tiny runnable example and practical advice on how to progress from hand-rolled code to production frameworks.
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chapters (4)
- 0:00Intro
- 1:20How can people learn machine learning without math
- 2:08Ellens message to new developers
- 3:40Skills you can learn elsewhere
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