Description: Probabilistic Deep Learning by Oliver Durr, Beate Sick, Elvis Murina Estimated delivery 3-12 business days Format Paperback Condition Brand New Description Probabilistic Deep Learning shows how probabilistic deep learning models gives readers the tools to identify and account for uncertainty and potential errors in their results. Starting by applying the underlying maximum likelihood principle of curve fitting to deep learning, readers will move on to using the Python-based Tensorflow Probability framework, and set up Bayesian neural networks that can state their uncertainties. Key Features · The maximum likelihood principle that underlies deep learning applications · Probabilistic DL models that can indicate the range of possible outcomes · Bayesian deep learning that allows for the uncertainty occurring in real-world situations · Applying probabilistic principles to variational auto-encoders Aimed at a reader experienced with developing machine learning or deep learning applications. About the technology Probabilistic deep learning models are better suited to dealing with the noise and uncertainty of real world data —a crucial factor for self-driving cars, scientific results, financial industries, and other accuracy-critical applications. Oliver DÜrr is professor for data science at the University of Applied Sciences in Konstanz, Germany. Beate Sick holds a chair for applied statistics at ZHAW, and works as a researcher and lecturer at the University of Zurich, and as a lecturer at ETH Zurich. Elvis Murina is a research assistant, responsible for the extensive exercises that accompany this book. DÜrr and Sick are both experts in machine learning and statistics. They have supervised numerous bachelors, masters, and PhD the seson the topic of deep learning, and planned and conducted several postgraduate and masters-level deep learning courses. All three authors have been working with deep learning methods since 2013 and have extensive experience in both teaching the topic and developing probabilistic deep learning models. Author Biography Oliver DÜrr is professor for data science at the University of Applied Sciences in Konstanz, Germany. Beate Sick holds a chair for applied statistics at ZHAW, and works as a researcher and lecturer at the University of Zurich, and as a lecturer at ETH Zurich. Elvis Murina is a research assistant, responsible for the extensive exercises that accompany this book. DÜrr and Sick are both experts in machine learning and statistics. They have supervised numerous bachelors, masters, and PhD the seson the topic of deep learning, and planned and conducted several postgraduate and masters-level deep learning courses. All three authors have been working with deep learning methods since 2013 and have extensive experience in both teaching the topic and developing probabilistic deep learning models. Details ISBN 1617296074 ISBN-13 9781617296079 Title Probabilistic Deep Learning Author Oliver Durr, Beate Sick, Elvis Murina Format Paperback Year 2021 Pages 252 Publisher Manning Publications GE_Item_ID:137757061; 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. Returns If you wish to return an item, please consult our Returns Policy as below: Please contact Customer Services and request "Return Authorisation" before you send your item back to us. Unauthorised returns will not be accepted. Returns must be postmarked within 4 business days of authorisation and must be in resellable condition. Returns are shipped at the customer's risk. We cannot take responsibility for items which are lost or damaged in transit. For purchases where a shipping charge was paid, there will be no refund of the original shipping charge. Additional Questions If you have any questions please feel free to Contact Us. Categories Baby Books Electronics Fashion Games Health & Beauty Home, Garden & Pets Movies Music Sports & Outdoors Toys
Price: 61.18 USD
Location: Fairfield, Ohio
End Time: 2024-09-19T06:15:12.000Z
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Restocking Fee: No
Return shipping will be paid by: Buyer
All returns accepted: Returns Accepted
Item must be returned within: 30 Days
Refund will be given as: Money Back
ISBN-13: 9781617296079
Book Title: Probabilistic Deep Learning
Number of Pages: 252 Pages
Language: English
Publication Name: Probabilistic Deep Learning
Publisher: Manning Publications Co. LLC
Publication Year: 2020
Subject: Intelligence (Ai) & Semantics, Neural Networks, Databases / Data Mining
Item Height: 1 in
Item Weight: 28.9 Oz
Type: Textbook
Subject Area: Computers
Item Length: 9.2 in
Author: Oliver Durr, Beate Sick, Elvis Murina
Item Width: 7.3 in
Format: Trade Paperback
