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This 185-page book unlocks the secrets of deep learning.
drive.google.com/file/d/188pV6F…
Foundations
> machine learning basics
> computation efficiency
> training methodologies
Deep Models
> activation functions
> pooling
> dropout
> normalization
> attention
Architectures
> MLPs
> CNNs
> attention
Applications
> image classification
> object detection
> speech recognition
> reinforcement learning
The Compute Schism
> prompt engineering
> quantization
> adapters
> model merging

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