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Author: Jen Wiggins
Publisher: Sourcebooks
ISBN: 9781728234687
Category : Family & Relationships
Languages : en
Pages : 32
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Book Description
Married AF: A Funny Marriage Guide for the Newlywed or Bride is the perfect gift for brides who live in the real world, where the realities of marriage are silly, exasperating, and infuriatingly funny. Full of familiar scenarios and pop culture references, even Grandma will appreciate its real take on topics from peeing in the wedding dress to aging gracefully with your other half. This beautifully illustrated book concludes with a useful twist by providing a gift register and space for friends and family to write encouraging words of advice and messages for the couple, making it the perfect keepsake. This is THE book to give if you're wondering what to get for a bridal shower gift, bachelorette party, engagement party, or wedding gift for brides.
Author: Jen Wiggins
Publisher: Sourcebooks
ISBN: 9781728234687
Category : Family & Relationships
Languages : en
Pages : 32
Get Book Here
Book Description
Married AF: A Funny Marriage Guide for the Newlywed or Bride is the perfect gift for brides who live in the real world, where the realities of marriage are silly, exasperating, and infuriatingly funny. Full of familiar scenarios and pop culture references, even Grandma will appreciate its real take on topics from peeing in the wedding dress to aging gracefully with your other half. This beautifully illustrated book concludes with a useful twist by providing a gift register and space for friends and family to write encouraging words of advice and messages for the couple, making it the perfect keepsake. This is THE book to give if you're wondering what to get for a bridal shower gift, bachelorette party, engagement party, or wedding gift for brides.
Author: United States. Air Force. Office of the Chief of Chaplains
Publisher:
ISBN:
Category : Government publications
Languages : en
Pages : 668
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Book Description
Author: Lei Chen
Publisher: Springer
ISBN: 3319111167
Category : Computers
Languages : en
Pages : 697
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Book Description
This book constitutes the refereed proceedings of the 16th Asia-Pacific Conference APWeb 2014 held in Changsha, China, in September 2014. The 34 full papers and 23 short papers presented were carefully reviewed and selected from 134 submissions. The papers address research, development and advanced applications of large-scale data management, web and search technologies, and information processing.
Author: J. Morris Chang
Publisher: Simon and Schuster
ISBN: 1617298042
Category : Computers
Languages : en
Pages : 334
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Book Description
Keep sensitive user data safe and secure without sacrificing the performance and accuracy of your machine learning models. In Privacy Preserving Machine Learning, you will learn: Privacy considerations in machine learning Differential privacy techniques for machine learning Privacy-preserving synthetic data generation Privacy-enhancing technologies for data mining and database applications Compressive privacy for machine learning Privacy-Preserving Machine Learning is a comprehensive guide to avoiding data breaches in your machine learning projects. You’ll get to grips with modern privacy-enhancing techniques such as differential privacy, compressive privacy, and synthetic data generation. Based on years of DARPA-funded cybersecurity research, ML engineers of all skill levels will benefit from incorporating these privacy-preserving practices into their model development. By the time you’re done reading, you’ll be able to create machine learning systems that preserve user privacy without sacrificing data quality and model performance. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Machine learning applications need massive amounts of data. It’s up to you to keep the sensitive information in those data sets private and secure. Privacy preservation happens at every point in the ML process, from data collection and ingestion to model development and deployment. This practical book teaches you the skills you’ll need to secure your data pipelines end to end. About the Book Privacy-Preserving Machine Learning explores privacy preservation techniques through real-world use cases in facial recognition, cloud data storage, and more. You’ll learn about practical implementations you can deploy now, future privacy challenges, and how to adapt existing technologies to your needs. Your new skills build towards a complete security data platform project you’ll develop in the final chapter. What’s Inside Differential and compressive privacy techniques Privacy for frequency or mean estimation, naive Bayes classifier, and deep learning Privacy-preserving synthetic data generation Enhanced privacy for data mining and database applications About the Reader For machine learning engineers and developers. Examples in Python and Java. About the Author J. Morris Chang is a professor at the University of South Florida. His research projects have been funded by DARPA and the DoD. Di Zhuang is a security engineer at Snap Inc. Dumindu Samaraweera is an assistant research professor at the University of South Florida. The technical editor for this book, Wilko Henecka, is a senior software engineer at Ambiata where he builds privacy-preserving software. Table of Contents PART 1 - BASICS OF PRIVACY-PRESERVING MACHINE LEARNING WITH DIFFERENTIAL PRIVACY 1 Privacy considerations in machine learning 2 Differential privacy for machine learning 3 Advanced concepts of differential privacy for machine learning PART 2 - LOCAL DIFFERENTIAL PRIVACY AND SYNTHETIC DATA GENERATION 4 Local differential privacy for machine learning 5 Advanced LDP mechanisms for machine learning 6 Privacy-preserving synthetic data generation PART 3 - BUILDING PRIVACY-ASSURED MACHINE LEARNING APPLICATIONS 7 Privacy-preserving data mining techniques 8 Privacy-preserving data management and operations 9 Compressive privacy for machine learning 10 Putting it all together: Designing a privacy-enhanced platform (DataHub)
Author: Linda M. Blum
Publisher: NYU Press
ISBN: 1479871540
Category : Family & Relationships
Languages : en
Pages : 319
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Book Description
Some 22 percent of American children today have some form of disability. In this highly important book, Linda Blum plunges us into the world of their worried mothers, deciphering labels and pills, fending off stigma, tirelessly advocating for their children. Married or alone, affluent or poor, such mothers often feel blamed and too rarely in the presence of real help. A carefully researched and deeply sensitive portrait of mothers on the Rx frontier.
Author:
Publisher:
ISBN:
Category : Aeronautics
Languages : en
Pages : 442
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Book Description
Author: Louise Pecquet du Bellet
Publisher:
ISBN:
Category : Reference
Languages : en
Pages : 910
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Book Description
Author: Sir John Hayward
Publisher:
ISBN:
Category : Great Britain
Languages : en
Pages : 204
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Book Description
Author:
Publisher:
ISBN:
Category : Income
Languages : en
Pages : 364
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Book Description
Author: United States. Bureau of the Census
Publisher:
ISBN:
Category : Housing
Languages : en
Pages : 96
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Book Description
