Description: Deep Learning and XAI Techniques for Anomaly Detection by Cher Simon, Jeff Barr Estimated delivery 3-12 business days Format Paperback Condition Brand New Description Deep Learning and XAI Techniques for Anomaly Detection shows you how to evaluate and create explainable models, leading to increased interpretability and trust in model predictions with better performance. Youll explore the fundamentals of deep learning, anomaly detection, and XAI using practical examples and self-assessment questions. Publisher Description Create interpretable AI models for transparent and explainable anomaly detection with this hands-on guidePurchase of the print or Kindle book includes a free PDF eBookKey FeaturesBuild auditable XAI models for replicability and regulatory complianceDerive critical insights from transparent anomaly detection modelsStrike the right balance between model accuracy and interpretabilityBook DescriptionDespite promising advances, the opaque nature of deep learning models makes it difficult to interpret them, which is a drawback in terms of their practical deployment and regulatory compliance.Deep Learning and XAI Techniques for Anomaly Detection shows you state-of-the-art methods thatll help you to understand and address these challenges. By leveraging the Explainable AI (XAI) and deep learning techniques described in this book, youll discover how to successfully extract business-critical insights while ensuring fair and ethical analysis.This practical guide will provide you with tools and best practices to achieve transparency and interpretability with deep learning models, ultimately establishing trust in your anomaly detection applications. Throughout the chapters, youll get equipped with XAI and anomaly detection knowledge thatll enable you to embark on a series of real-world projects. Whether you are building computer vision, natural language processing, or time series models, youll learn how to quantify and assess their explainability.By the end of this deep learning book, youll be able to build a variety of deep learning XAI models and perform validation to assess their explainability.What you will learnExplore deep learning frameworks for anomaly detectionMitigate bias to ensure unbiased and ethical analysisIncrease your privacy and regulatory compliance awarenessBuild deep learning anomaly detectors in several domainsCompare intrinsic and post hoc explainability methodsExamine backpropagation and perturbation methodsConduct model-agnostic and model-specific explainability techniquesEvaluate the explainability of your deep learning modelsWho this book is forThis book is for anyone who aspires to explore explainable deep learning anomaly detection, tenured data scientists or ML practitioners looking for Explainable AI (XAI) best practices, or business leaders looking to make decisions on trade-off between performance and interpretability of anomaly detection applications. A basic understanding of deep learning and anomaly detection–related topics using Python is recommended to get the most out of this book. Author Biography Cher Simon is a principal solutions architect specializing in artificial intelligence, machine learning, and data analytics at AWS. Cher has 20 years of experience in architecting enterprise-scale, data-driven, and AI-powered industry solutions. Besides building cloud-native solutions in her day-to-day role with customers, Cher is also an avid writer and a frequent speaker at AWS conferences. Details ISBN 180461775X ISBN-13 9781804617755 Title Deep Learning and XAI Techniques for Anomaly Detection Author Cher Simon, Jeff Barr Format Paperback Year 2023 Pages 218 Publisher Packt Publishing Limited GE_Item_ID:141389432; 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: 59.92 USD
Location: Fairfield, Ohio
End Time: 2024-10-30T03:23:50.000Z
Shipping Cost: 0 USD
Product Images
Item Specifics
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: 9781804617755
Book Title: Deep Learning and XAI Techniques for Anomaly Detection
Number of Pages: 218 Pages
Publication Name: Deep Learning and XAI Techniques for Anomaly Detection : Integrating Theory and Practice of Explainable Deep Learning Anomaly Detection
Language: English
Publisher: Packt Publishing, The Limited
Subject: Data Modeling & Design, Intelligence (Ai) & Semantics, General, Information Technology
Publication Year: 2023
Type: Textbook
Item Length: 3.6 in
Author: Cher Simon
Subject Area: Computers, Science
Item Width: 3 in
Format: Trade Paperback
