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Deep learning regularization: Prevent overfitting effectively explained
Regularization in Deep Learning is very important to overcome overfitting. When your training accuracy is very high, but test ...
For about a decade, computer engineer Kerem Çamsari employed a novel approach known as probabilistic computing. Based on probabilistic bits (p-bits), it’s used to solve an array of complex ...
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