Microservices for Machine Learning: Design, implement, and manage high-performance ML systems with microservicesКНИГИ » ПРОГРАММИНГ
Название: Microservices for Machine Learning: Design, implement, and manage high-performance ML systems with microservices Автор: Rohit Ranjan Издательство: BPB Publications Год: 2024 Страниц: 966 Язык: английский Формат: pdf, epub, mobi Размер: 10.1 MB
Empowering AI innovations: The fusion of microservices and ML.
Key Features: - Microservices and ML fundamentals, advancements, and practical applications in various industries. - Simplify complex ML development with distributed and scalable microservices architectures. - Discover real-world scenarios illustrating the fusion of microservices and ML, showcasing AI's impact across industries.
Description: Explore the link between microservices and ML in Microservices for Machine Learning. Through this book, you will learn to build scalable systems by understanding modular software construction principles. You will also discover ML algorithms and tools like TensorFlow and PyTorch for developing advanced models.
It equips you with the technical know-how to design, implement, and manage high-performance ML applications using microservices architecture. It establishes a foundation in microservices principles and core ML concepts before diving into practical aspects. You will learn how to design ML-specific microservices, implement them using frameworks like Flask, and containerize them with Docker for scalability. Data management strategies for ML are explored, including techniques for real-time data ingestion and data versioning. This book also addresses crucial aspects of securing ML microservices and using CI/CD practices to streamline development and deployment. Finally, you will discover real-world use cases showcasing how ML microservices are revolutionizing various industries, alongside a glimpse into the exciting future trends shaping this evolving field.
Additionally, you will learn how to implement ML microservices with practical examples in Java and Python. This book merges software engineering and AI, guiding readers through modern development challenges. It is a guide for innovators, boosting efficiency and leading the way to a future of impactful technology solutions.
In the realm of software development, the confluence of microservices and Machine Learning (ML) represents a frontier of innovation, offering new paradigms for building dynamic, resilient, and intelligent applications. This book is a culmination of extensive research and practical insights aimed at unraveling the complexities and unleashing the potential of integrating microservices with ML.
Microservices architecture, with its promise of scalability, flexibility, and robustness, has revolutionized how we conceive and implement software solutions. When intertwined with the predictive power and adaptability of ML, it paves the way for creating systems that not only excel in functionality but also thrive on change and continuous improvement.
The journey through these pages is designed to be both enlightening and practical. We begin by setting a solid foundation, introducing you to the essential concepts and benefits of microservices and how they synergize with ML. As we navigate through the chapters, you will encounter a blend of theoretical discussions, practical examples, and insightful case studies, each chosen to illuminate different facets of building and deploying AI-enhanced microservices.
What you will learn: - Master the principles of microservices architecture for scalable software design. - Deploy ML microservices using cloud platforms like AWS and Azure for scalability. - Ensure ML microservices security with best practices in data encryption and access control. - Utilize Docker and Kubernetes for efficient microservice containerization and orchestration. - Implement CI/CD pipelines for automated, reliable ML model deployments.
Who this book is for: This book is for data scientists, ML engineers, data engineers, DevOps team, and cloud engineers who are responsible for delivering real-time, accurate, and reliable ML models into production.
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Building Server-side and Microservices with Go Название: Building Server-side and Microservices with Go: Building Modern Backends and Microservices Using Go, Docker and Kubernetes Автор: Dusan...
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Microservices for Machine Learning: Design, implement, and manage high-performance ML systems with microservices 
