What are some optimization techniques for TensorFlow.js?
There are several techniques to optimize TensorFlow.js models, including model pruning, quantization, and using WebGL for faster computations.
Can you explain model pruning?
Model pruning involves removing weights from a model that contribute little to its output, which reduces the model size and speeds up inference.
What is quantization?
Quantization reduces the precision of the numbers used in the model, which can significantly decrease the model size and improve performance without a major loss in accuracy.
How does using WebGL help with performance?
WebGL allows TensorFlow.js to leverage the GPU for computations, which can greatly enhance performance compared to CPU-only execution.
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