Probabilistic deep learning with Python, Keras, and TensorFlow Probability
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...
| Main Authors: | , , |
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| Format: | eBook |
| Language: | English |
| Published: |
Shelter Island, New York
Manning Publications
2020
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| Subjects: | |
| Online Access: | |
| Collection: | O'Reilly - Collection details see MPG.ReNa |
| Summary: | 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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| Item Description: | "Exercises in Jupyter Notebooks"--Cover |
| Physical Description: | 1 online resource |
| ISBN: | 163835040X 1617296074 9781638350408 |