Tag: ml-engineering
All the articles with the tag "ml-engineering".
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Gradient Descent and Backpropagation: How a Network Actually Learns
How gradient descent uses the loss to update weights, and how backpropagation computes the gradients that make it possible.
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Loss Functions: How a Neural Network Knows It's Wrong
What loss functions are, how MSE and cross-entropy work, and why picking the wrong one breaks your model even if everything else is right.
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Activation Functions: Why ReLU, GELU, and SiLU Exist
Why stacking linear layers isn't enough, and how activation functions like ReLU, GELU, and SiLU give neural networks their power.
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What is a Neural Network?
A neural network explained from scratch - neurons, weights, layers, and the forward pass - no ML background required.