Description: Enhancing Deep Learning with Bayesian Inference by Matt Benatan, Jochem Gietema, Marian Schneider Estimated delivery 3-12 business days Format Paperback Condition Brand New Description This book provides a comprehensive introduction to Bayesian deep learning methods for machine learning researchers and practitioners. It discusses the importance of uncertainty in machine learning, covers numerous methods for uncertainty-aware deep networks, and provides detailed code examples in Python to assist you throughout your exploration. Publisher Description Develop Bayesian Deep Learning models to help make your own applications more robust.Key FeaturesGain insights into the limitations of typical neural networksAcquire the skill to cultivate neural networks capable of estimating uncertaintyDiscover how to leverage uncertainty to develop more robust machine learning systemsBook DescriptionDeep learning has an increasingly significant impact on our lives, from suggesting content to playing a key role in mission- and safety-critical applications. As the influence of these algorithms grows, so does the concern for the safety and robustness of the systems which rely on them. Simply put, typical deep learning methods do not know when they dont know.The field of Bayesian Deep Learning contains a range of methods for approximate Bayesian inference with deep networks. These methods help to improve the robustness of deep learning systems as they tell us how confident they are in their predictions, allowing us to take more in how we incorporate model predictions within our applications.Through this book, you will be introduced to the rapidly growing field of uncertainty-aware deep learning, developing an understanding of the importance of uncertainty estimation in robust machine learning systems. You will learn about a variety of popular Bayesian Deep Learning methods, and how to implement these through practical Python examples covering a range of application scenarios.By the end of the book, you will have a good understanding of Bayesian Deep Learning and its advantages, and you will be able to develop Bayesian Deep Learning models for safer, more robust deep learning systems.What you will learnUnderstand advantages and disadvantages of Bayesian inference and deep learningUnderstand the fundamentals of Bayesian Neural NetworksUnderstand the differences between key BNN implementations/approximationsUnderstand the advantages of probabilistic DNNs in production contextsHow to implement a variety of BDL methods in Python codeHow to apply BDL methods to real-world problemsUnderstand how to evaluate BDL methods and choose the best method for a given taskLearn how to deal with unexpected data in real-world deep learning applicationsWho this book is forThis book will cater to researchers and developers looking for ways to develop more robust deep learning models through probabilistic deep learning. Youre expected to have a solid understanding of the fundamentals of machine learning and probability, along with prior experience working with machine learning and deep learning models. Author Biography Matt Benatan is a Principal Research Scientist at Sonos and a Simon Industrial Fellow at the University of Manchester. His work involves research in robust multimodal machine learning, uncertainty estimation, Bayesian optimization, and scalable Bayesian inference. Jochem Gietema is an Applied Scientist at Onfido in London where he has developed and deployed several patented solutions related to anomaly detection, computer vision, and interactive data visualisation. Marian Schneider is an applied scientist in machine learning. His work involves developing and deploying applications in computer vision, ranging from brain image segmentation and uncertainty estimation to smarter image capture on mobile devices. Details ISBN 180324688X ISBN-13 9781803246888 Title Enhancing Deep Learning with Bayesian Inference Author Matt Benatan, Jochem Gietema, Marian Schneider Format Paperback Year 2023 Pages 386 Publisher Packt Publishing Limited GE_Item_ID:143178996; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. NOTE: We are unable to offer combined shipping for multiple items purchased. This is because our items are shipped from different locations. 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Price: 69.8 USD
Location: Fairfield, Ohio
End Time: 2024-11-12T04:08:37.000Z
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ISBN-13: 9781803246888
Book Title: Enhancing Deep Learning with Bayesian Inference
Number of Pages: 249 Pages
Language: English
Publication Name: Enhancing Deep Learning with Bayesian Inference : Create More Powerful, Robust Deep Learning Systems with Bayesian Deep Learning in Python
Publisher: Packt Publishing, The Limited
Publication Year: 2023
Subject: Neural Networks, General
Type: Textbook
Author: Marian Schneider, Matt Benatan, Jochem Gietema
Subject Area: Computers, Science
Item Length: 92.5 in
Item Width: 75 in
Format: Trade Paperback
