Applied Machine Learning and High-Performance Computing on AWS: Accelerate the development of machine learning applications following architectural best practices

Price: $46.99 – $44.85
(as of Nov 24,2024 13:31:20 UTC – Details)

Publisher ‏ : ‎ Packt Publishing (December 30, 2022)
Language ‏ : ‎ English
Paperback ‏ : ‎ 382 pages
ISBN-10 ‏ : ‎ 1803237015
ISBN-13 ‏ : ‎ 978-1803237015
Item Weight ‏ : ‎ 1.47 pounds
Dimensions ‏ : ‎ 9.25 x 7.52 x 0.8 inches

In today’s rapidly evolving technological landscape, the intersection of machine learning and high-performance computing has become increasingly vital for organizations looking to gain a competitive edge. Leveraging the power of AWS, developers can accelerate the development of machine learning applications while adhering to architectural best practices.

By harnessing the scalability and flexibility of AWS’s cloud infrastructure, developers can easily access a wide range of machine learning tools and services to build, train, and deploy models with ease. With AWS’s powerful compute resources, organizations can quickly process large datasets and run complex algorithms to train models faster and more efficiently.

To ensure optimal performance and scalability, it is essential to follow architectural best practices when designing machine learning applications on AWS. This includes using services like Amazon SageMaker for end-to-end machine learning workflows, Amazon EC2 for high-performance computing, and Amazon S3 for storing and accessing data. By adopting a well-architected approach, developers can ensure their applications are secure, reliable, and cost-effective.

Overall, by combining the capabilities of machine learning and high-performance computing on AWS, organizations can accelerate the development of innovative applications that drive business growth and success. Embracing best practices in architecture will enable developers to build robust and scalable solutions that leverage the full potential of AWS’s cloud infrastructure.
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