^DOWNLOAD E.B.O.O.K.# Probabilistic Deep Learnin

<i>Probabilistic Deep Learning</i> 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.<br /><br /><b>Summary</b><br /> <i>Probabilistic Deep Learning: With Python, Keras and TensorFlow Probability</i> teaches the increasingly popular probabilistic approach to deep learning that allows you to refine your results more quickly and accurately without much trial-and-error testing. Emphasizing practical techniques that use the Python-based Tensorflow Probability Framework, you’ll learn to build highly-performant deep learning applications that can reliably handle the noise and uncertainty of real-world data.<br /> <br />Purchase of the print book includes a free eBook in PDF, Kindle, and