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High Performance with Java

You're reading from   High Performance with Java Discover strategies and best practices to develop high performance Java applications

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Product type Paperback
Published in Jul 2024
Publisher Packt
ISBN-13 9781835469736
Length 306 pages
Edition 1st Edition
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Author (1):
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Dr. Edward Lavieri Jr. Dr. Edward Lavieri Jr.
Author Profile Icon Dr. Edward Lavieri Jr.
Dr. Edward Lavieri Jr.
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Table of Contents (26) Chapters Close

Preface 1. Part 1: Code Optimization FREE CHAPTER
2. Chapter 1: Peeking Inside the Java Virtual Machine 3. Chapter 2: Data Structures 4. Chapter 3: Optimizing Loops 5. Chapter 4: Java Object Pooling 6. Chapter 5: Algorithm Efficiencies 7. Part 2: Memory Optimization and I/O Operations
8. Chapter 6: Strategic Object Creation and Immutability 9. Chapter 7: String Objects 10. Chapter 8: Memory Leaks 11. Part 3: Concurrency and Networking
12. Chapter 9: Concurrency Strategies and Models 13. Chapter 10: Connection Pooling 14. Chapter 11: Hypertext Transfer Protocols 15. Part 4: Frameworks, Libraries, and Profiling
16. Chapter 12: Frameworks for Optimization 17. Chapter 13: Performance-Focused Libraries 18. Chapter 14: Profiling Tools 19. Part 5: Advanced Topics
20. Chapter 15: Optimizing Your Database and SQL Queries 21. Chapter 16: Code Monitoring and Maintenance 22. Chapter 17: Unit and Performance Testing 23. Chapter 18: Leveraging Artificial Intelligence (AI) for High-Performance Java Applications 24. Index 25. Other Books You May Enjoy

AI integration

AI requires significant computing power. Leveraging the elastic cloud computing of cloud service providers is commonplace. There are also open source platforms that offer pre-built models for use. Let’s take a brief look at AI services from the three largest cloud service providers (AWS, Microsoft Azure, and Google Cloud) and two open source platforms (Apache Spark MLlib and TensorFlow for Java), starting with the three cloud service providers.

  • AWS AI Services: Amazon’s cloud platform offers an entire suite of AI services that include SageMaker for building training models, Amazon Rekognition for image and video analysis, and Amazon Comprehend for NLP.
  • Microsoft Azure AI: Microsoft offers similar AI tools to AWS, which include Azure ML for ML model development, Bot Service for creating AI-powered chatbots, and Cognitive Services, containing pre-built AI functionality.
  • Google Cloud AI: Google Cloud, like Amazon and Microsoft, offers a suite...
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