McConnaughy, Tim

McNutt, Steve

Miles, Christopher

A pragmatic guide to acing the AWS ANS-C01 exam

AWS Certified Advanced Networking – Specialty (ANS-C01) Certification Guide

Malavasi, Alexandre

A project-based guide to building web applications with ASP.NET Core 9 and JavaScript frameworks

Modern Full-Stack Web Development with ASP.NET Core

Despoudis, Theofanis

Build clean and scalable apps with proven patterns and expert insights

TypeScript 5 Design Patterns and Best Practices

Verma, Jatin

Build a solid foundation in Snowflake to pass the SnowPro Core exam on the first attempt

SnowPro Core Certification Study Guide

Mukherjee, Amit

Casalaina, Marco

Saladi, Adithya

A practical guide to unlocking generative AI-powered innovation with Azure OpenAI

Azure OpenAI Essentials

Loredo, Robert

Write your own practical quantum programs with Python

Learn Quantum Computing with Python and IBM Quantum

Najlaa, Najihah

Master video editing with expert tips, techniques, and workflows

The Complete Guide to Adobe Premiere Pro 2025

Makhija, Jagjeet Singh

Odunukwe, Charles

Boost your skills with expert insights and certification-ready strategies for Microsoft analytics

Implementing Analytics Solutions Using Microsoft Fabric—DP-600 Exam Study Guide

Belmansour, Tidjani

Brady, Damian

A step-by-step guide to developing cross-platform CLI apps—from coding and testing to deployment

Building CLI Applications with C# and .NET

Apperson, Lem

Weinberger, Jonathan

Leverage C# scripting in Unity to create immersive games and VR experiences

Unity 6 Game Development with C# Scripting

A use-case-driven approach to building and protecting ML pipelines from privacy and security threats

Privacy-Preserving Machine Learning

<span xml:lang="en">Privacy-Preserving Machine Learning: A use-case-driven approach to building and protecting ML pipelines from privacy and security threats</span>

Aravilli, Srinivasa Rao

Hamilton, Sam

Gain hands-on experience in data privacy and privacy-preserving machine learning with open-source ML frameworks, while exploring techniques and algorithms to protect sensitive data from privacy breaches Key FeaturesUnderstand machine learning privacy risks and employ machine learning algorithms to safeguard data against breachesDevelop and deploy privacy-preserving ML pipelines using open-source frameworksGain insights into confidential computing and its role in countering memory-based data attacksPurchase of the print or Kindle book includes a free PDF eBookBook Description– In an era of...

Gain hands-on experience in data privacy and privacy-preserving machine learning with open-source ML frameworks, while exploring techniques and...

Privacy-Preserving Machine Learning: A use-case-driven...

Privacy-Preserving Machine Learning: A use-case-driven approach to building and protecting ML pipelines from privacy and security threats

Format

Privacy-Preserving Machine Learning: A use-case-driven approach to building and protecting ML pipelines from privacy and security threats

Srinivasa Rao Aravilli

Sam Hamilton

Les gens lisent aussi