with Python, Keras, and TensorFlow Probability Dürr, Oliver creator author. Sick, Beate author. Murina, Elvis author. text nyu New York Manning Publications Co. 2020 2020 monographic eng

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xviii, 274 pages : illustrations ; 24 cm "A hands-on guide to the principles that support neural networks"-- Part 1, Basics of deep learning. Introduction to probabilistic deep learning ; Neural network architectures ; Principles of curve fitting -- Part 2, Maximum likelihood approaches for probabilistic DL models. Building loss functions with the likelihood approach ; Probabilistic deep learning models with TensorFlow Probability ; Probabilistic deep learning models in the wild -- Part 3, Bayesian approaches for probabilistic DL models. Bayesian learning ; Bayesian neural networks. "For experience machine learning developers"--Page 4 of cover. Oliver Dürr, Beate Sick ; with Elvis Murina. Includes index. "Exercises in Jupyter Notebooks"--Page 1 of cover. CSE ps REF Omni concept Machine learning Neural networks (Computer science) Machine learning Neural networks (Computer science) 006.31 D9651p 9781617296079 YDX 260602 20260602155154.0 57811 eng