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OverviewFull Product DetailsAuthor: Mani Khanuja , Farooq Sabir , Shreyas Subramanian , Trenton PotgieterPublisher: Packt Publishing Limited Imprint: Packt Publishing Limited ISBN: 9781803237015ISBN 10: 1803237015 Pages: 382 Publication Date: 30 December 2022 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: In stock  We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately. Table of ContentsTable of Contents High-Performance Computing Fundamentals Data Management and Transfer Compute and Networking Data Storage Data Analysis Distributed Training of Machine Learning Models Deploying Machine Learning Models at Scale Optimizing and Managing Machine Learning Models for Edge Deployment Performance Optimization for Real-Time Inference Data Visualization Computational Fluid Dynamics Genomics Autonomous Vehicles Numerical OptimizationReviewsAuthor InformationMani 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 edge, and automating the complete machine learning lifecycle to build repeatable and scalable applications. Farooq Sabir is a research and development expert in machine learning, data science, big data, predictive analytics, computer vision, image, and video processing. He also has 10+ years of professional experience. Shreyas Subramanian helps AWS customers build and fine tune large-scale machine learning and deep learning models, and rearchitect solutions to help improve security, scalability, and efficiency of machine learning platforms. He also specializes in setting up massively parallel distributed training, hyperparameter optimization, reinforcement learning solutions, and provides reusable architecture templates to solve AI and optimization use cases. 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, 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 these from engineering to executive levels. Tab Content 6Author Website:Countries AvailableAll regions |
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