OUTTA Basic — Following the Time Axis in RNNs and Seq2Seq
I revisited hidden states, sequence shapes, train-test divergence, and teacher forcing through retained RNN learning curves.
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Discriminative Models
Separate learning paths for discriminative AI, vision, and generative models.
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OUTTA Basic — Neural Networks for Function Approximation and Nonlinear Classification
I compared sigmoid-basis function approximation, spiral decision boundaries, and a stalled classifier to understand network capacity and training failure.
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