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› model.train()|
tokens: 4,096
epoch 42/50
accuracy: 98.7%
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AI in action

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Every course brings you inside the systems you're building. Real inference, real data, real projects.

Audio · speech · NLP

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Watch a transformer process voice, text and images in real time inside every technical course.

◉ REC · 00:04:12 16 kHz · MEL
Training loss

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Classifier output

What the model sees

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agent.py
$ python agent.py --task=summarize
✓ loading model llama-3-8b...
✓ context loaded (12,340 tok)
→ inference: 142 tok/s
output: "Ready."
Attention is all you need

Transformer, decoded

Peek inside multi-head attention. Trace how tokens flow, weights fire, and predictions form, animated inside every LLM lecture.

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