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Cloud-Native Quant Trading: Building Scalable AI Systems with AWS, GCP, and Azure: Design, Deploy, and Scale Intelligent Trading Architectures with Cl
Paperback
Publisher: Independently Published
Published: Sep 4 2025
Pages: 634
Weight: 1.84
Height: 1.28 Width: 6.00 Depth: 9.00
Language: English
Financial markets demand speed, intelligence, and scalability. Cloud-Native Quant Trading equips you with the knowledge and tools to harness the full power of modern cloud infrastructure for AI-driven trading. Designed for quant professionals, data scientists, and algorithmic traders, this book shows you how to design, deploy, and optimize trading systems that scale effortlessly across AWS, GCP, and Azure.
Inside, you'll explore:
Cloud-native architectures tailored for high-frequency and low-latency trading.
Real-time data pipelines for market data ingestion, feature engineering, and execution.
AI model integration with LSTMs, Transformers, and reinforcement learning agents.
Scalable infrastructure strategies using Kubernetes, serverless computing, and distributed storage.
Cross-cloud deployment for risk management, redundancy, and global reach.
Security and compliance frameworks essential for institutional-grade trading systems.
From setting up elastic environments to building robust AI pipelines, this book bridges the gap between quantitative finance and cutting-edge cloud engineering. By the end, you'll have a practical blueprint for trading systems that are not only intelligent, but built to thrive in the fast-changing, globalized market landscape.
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Forbeck, Marty
Forbeck, Matt
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The Problem with Personalization: How Advertisers Learned to Make and Break Us from Ancient Times to the AI Age
Turow, Joseph
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The Devops Handbook, 2nd Edition: How to Create World-Class Agility, Reliability, & Security in Technology Organizations
Humble, Jez
Debois, Patrick
Kim, Gene
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You to the Power of Two: Redefining Human Potential in the Age of Identic AI
Bradley, Joseph
Tapscott, Don
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The Death of Expertise: The Campaign Against Established Knowledge and Why It Matters
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Graphic Artists Guild Handbook, 17th Edition: Pricing & Ethical Guidelines
The Graphic Artists Guild
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Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications
Huyen, Chip
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Artificial Intelligence All-In-One for Dummies
Massaron, Luca
Minnick, Chris
Mueller, John Paul
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The AI Ultimatum: Preparing for a World of Intelligent Machines and Radical Transformation
Brown, Steve
Hill, Paul
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RHCSA Red Hat Enterprise Linux 10: Training and Exam Preparation Guide (EX200), Fourth Edition
Ghori, Asghar
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The Coming Wave: Technology, Power, and the Twenty-First Century's Greatest Dilemma
Suleyman, Mustafa
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AI for Educators: Learning Strategies, Teacher Efficiencies, and a Vision for an Artificial Intelligence Future
Miller, Matt
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The Fourth Intelligence Revolution: The Future of Espionage and the Battle to Save America
Vinci, Anthony
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More Human: How the Power of AI Can Transform the Way You Lead
Hougaard, Rasmus
Carter, Jacqueline
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Hbr's 10 Must Reads on Artificial Intelligence, Updated and Expanded (Featuring How AI Can Help Managers Think Through Problems by Elisa Farri and Gab
Agrawal, Ajay
Review, Harvard Business
Davenport, Thomas H.
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Microsoft 365 Excel All-In-One for Dummies
Ringstrom, David H.
Alexander, Michael
Kusleika, Dick
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Building Applications with AI Agents: Designing and Implementing Multiagent Systems
Albada, Michael
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Navigeren door het labyrint: Een handleiding voor het beheer van data
Sebastian-Coleman, Laura
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The Technological Republic: Hard Power, Soft Belief, and the Future of the West
Karp, Alexander C.
Zamiska, Nicholas W.
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What Is Intelligence?: Lessons from AI about Evolution, Computing, and Minds
Aguera Y. Arcas, Blaise
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Comptia A+ Complete Study Guide, 2-Volume Set: Volume 1 Core 1 Exam 220-1201 and Volume 2 Core 2 Exam 220-1202
Buhagiar, Jon
Docter, Quentin
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The Experimentation Machine: Finding Product-Market Fit in the Age of AI
Bussgang, Jeffrey J.
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R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
Grolemund, Garrett
Cetinkaya-Rundel, Mine
Wickham, Hadley
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Prediction Machines, Updated and Expanded: The Simple Economics of Artificial Intelligence
Goldfarb, Avi
Agrawal, Ajay
Gans, Joshua
Hardcover