Deep learning
Machine learning with neural networks of many layers. It is behind speech recognition, image recognition and every modern language model.
01In short
Machine learning with neural networks of many layers. It is behind speech recognition, image recognition and every modern language model.
02Video
slot · videoDeep learning in 90 secondsadd: GUIDES['deep-learning'].video
03Guide
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A step-by-step guide for “Deep learning” goes here. Suggested outline:
- What it is — in one paragraph
- Why it matters in production
- How to do it — 3 to 7 steps
- Pitfalls we see in the field
04Checklist
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Four to eight things a team can tick before go-live.
05FAQ
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The three questions clients actually ask about “Deep learning”.
06Related terms
BasicsNeural networkA model built from layers of simple connected units whose weights are adjusted during training. Loosely inspired by the brain; mathematically, a lot of matrix multiplication.BasicsTransformerThe neural-network architecture behind today’s language models, introduced in 2017. Its attention mechanism lets every token weigh every other token in the context.
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