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Applied Machine Learning and High-Performance Computing on AWS Cover

Applied Machine Learning and High-Performance Computing on AWS

Accelerate the development of machine learning applications following architectural best practices

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|May 2024
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Authors

Khanuja Mani :

Mani Khanuja is a seasoned IT professional with over 17 years of software engineering experience. She has successfully led machine learning and artificial intelligence projects in various domains, such as forecasting, computer vision, and natural language processing. At AWS, she helps customers to build, train, and deploy large machine learning models at scale. She also specializes in data preparation, distributed model training, performance optimization, machine learning at the edge, and automating the complete machine learning life cycle to build repeatable and scalable applications.Sabir Farooq :

Farooq Sabir is a research and development expert in machine learning, data science, big data, predictive analytics, computer vision, and image and video processing. He has over 10 years of professional experience.Subramanian Shreyas :

Shreyas Subramanian helps AWS customers build and fine-tune large-scale machine learning and deep learning models, and rearchitect solutions to help improve the security, scalability, and efficiency of machine learning platforms. He also specializes in setting up massively parallel distributed training, hyperparameter optimization, and reinforcement learning solutions, and provides reusable architecture templates to solve AI and optimization use cases.Potgieter Trenton :

Trenton Potgieter is an expert technologist with 25 years of both local and international experience across multiple aspects of an organization; from IT to sales, engineering, and consulting, on the cloud and on-premises. He has a proven ability to analyze, assess, recommend, and design appropriate solutions that meet key business criteria, as well as present and teach them from engineering to executive levels.

PDF ISBN: 978-1-80324-444-0
Publisher: Packt Publishing Limited
Copyright owner: © 2022 Packt Publishing Limited
Publication date: 2024
Language: English
Pages: 382