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By Oliver Duerr, Beate Sick, Elvis Murina

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Probabilistic Deep Learning is a hands-on guide to the principles that support neural networks. Learn to improve network performance with the right distribution for different data types, and discover Bayesian variants that can state their own uncertainty to increase accuracy. This book provides easy-to-apply code and uses popular frameworks to keep you focused on practical applications.

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Probabilistic Deep Learning: With Python, Keras and TensorFlow Probability teaches the increasingl...

Probabilistic Deep Learning: With Python, Keras and TensorFlow Probability

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