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Serverless Machine Learning With Amazon Redshift Ml

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Serverless Machine Learning With Amazon Redshift Ml

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Author : Debu Panda
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-08-30

Serverless Machine Learning With Amazon Redshift Ml written by Debu Panda and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-30 with Computers categories.

Supercharge and deploy Amazon Redshift Serverless, train and deploy machine learning models using Amazon Redshift ML, and run inference queries at scale Key Features Leverage supervised learning to build binary classification, multi-class classification, and regression models Learn to use unsupervised learning using the K-means clustering method Master the art of time series forecasting using Redshift ML Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionAmazon Redshift Serverless enables organizations to run petabyte-scale cloud data warehouses quickly and in a cost-effective way, enabling data science professionals to efficiently deploy cloud data warehouses and leverage easy-to-use tools to train models and run predictions. This practical guide will help developers and data professionals working with Amazon Redshift data warehouses to put their SQL knowledge to work for training and deploying machine learning models. The book begins by helping you to explore the inner workings of Redshift Serverless as well as the foundations of data analytics and types of data machine learning. With the help of step-by-step explanations of essential concepts and practical examples, you’ll then learn to build your own classification and regression models. As you advance, you’ll find out how to deploy various types of machine learning projects using familiar SQL code, before delving into Redshift ML. In the concluding chapters, you’ll discover best practices for implementing serverless architecture with Redshift. By the end of this book, you’ll be able to configure and deploy Amazon Redshift Serverless, train and deploy machine learning models using Amazon Redshift ML, and run inference queries at scale.What you will learn Utilize Redshift Serverless for data ingestion, data analysis, and machine learning Create supervised and unsupervised models and learn how to supply your own custom parameters Discover how to use time series forecasting in your data warehouse Create a SageMaker endpoint and use that to build a Redshift ML model for remote inference Find out how to operationalize machine learning in your data warehouse Use model explainability and calculate probabilities with Amazon Redshift ML Who this book is forData scientists and machine learning developers working with Amazon Redshift who want to explore its machine-learning capabilities will find this definitive guide helpful. A basic understanding of machine learning techniques and working knowledge of Amazon Redshift is needed to make the most of this book.

Serverless Machine Learning With Amazon Redshift Ml

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Author : Debu Panda
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-08-30

Serverless Machine Learning With Amazon Redshift Ml

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Author : Debu Panda
language : en
Publisher:
Release Date : 2023-03

Serverless Machine Learning With Amazon Redshift Ml written by Debu Panda and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03 with categories.

This book helps you implement end-to-end serverless architectures for ingestion, analytics, and machine learning using Redshift Serverless and Redshift ML.

Amazon Redshift Cookbook

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Author : Shruti Worlikar
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-04-25

Amazon Redshift Cookbook written by Shruti Worlikar and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-25 with Computers categories.

Set up a petabyte-scale, cloud-based data warehouse that is burstable and built to scale for end-to-end analytical solutions Key Features Learn how to translate familiar data warehousing concepts into Redshift implementation Use impressive Redshift features to optimize development, productionizing, and operation processes Find out how to use advanced features such as concurrency scaling, Redshift Spectrum, and federated queries Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionAmazon Redshift Cookbook offers comprehensive guidance for leveraging AWS's fully managed cloud data warehousing service. Whether you're building new data warehouse workloads or migrating traditional on-premises platforms to the cloud, this essential resource delivers proven implementation strategies. Written by AWS specialists, these easy-to-follow recipes will equip you with the knowledge to successfully implement Amazon Redshift-based data analytics solutions using established best practices. The book focuses on Redshift architecture, showing you how to perform database administration tasks on Redshift. You'll learn how to optimize your data warehouse to quickly execute complex analytic queries against very large datasets. The book covers recipes to help you take full advantage of Redshift's columnar architecture and managed services. You'll discover how to deploy fully automated and highly scalable extract, transform, and load (ETL) processes, helping you minimize the operational effort that you invest in managing regular ETL pipelines and ensuring the timely and accurate refreshing of your data warehouse. By the end of this Redshift book, you'll be able to implement a Redshift-based data analytics solution by adopting best-practice approaches for solving commonly faced problems.What you will learn Integrate data warehouses with data lakes using AWS features Create end-to-end analytical solutions from sourcing to consumption Utilize Redshift's security for strict business requirements Apply architectural insights with analytical recipes Discover big data best practices for managed solutions Enable data sharing for data mesh and hub-and-spoke architectures Explore Redshift ML and generative AI with Amazon Q Who this book is for This book is for anyone involved in architecting, implementing, and optimizing an Amazon Redshift data warehouse, including data warehouse developers, data analysts, database administrators, data engineers, and data scientists. Basic knowledge of data warehousing, database systems, as well as cloud concepts and familiarity with Redshift is beneficial.

Amazon Redshift The Definitive Guide

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Author : Rajesh Francis
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2023-10-03

Amazon Redshift The Definitive Guide written by Rajesh Francis and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-03 with Computers categories.

Amazon Redshift powers analytic cloud data warehouses worldwide, from startups to some of the largest enterprise data warehouses available today. This practical guide thoroughly examines this managed service and demonstrates how you can use it to extract value from your data immediately, rather than go through the heavy lifting required to run a typical data warehouse. Analytic specialists Rajesh Francis, Rajiv Gupta, and Milind Oke detail Amazon Redshift's underlying mechanisms and options to help you explore out-of-the box automation. Whether you're a data engineer who wants to learn the art of the possible or a DBA looking to take advantage of machine learning-based auto-tuning, this book helps you get the most value from Amazon Redshift. By understanding Amazon Redshift features, you'll achieve excellent analytic performance at the best price, with the least effort. This book helps you: Build a cloud data strategy around Amazon Redshift as foundational data warehouse Get started with Amazon Redshift with simple-to-use data models and design best practices Understand how and when to use Redshift Serverless and Redshift provisioned clusters Take advantage of auto-tuning options inherent in Amazon Redshift and understand manual tuning options Transform your data platform for predictive analytics using Redshift ML and break silos using data sharing Learn best practices for security, monitoring, resilience, and disaster recovery Leverage Amazon Redshift integration with other AWS services to unlock additional value

Mlops With Red Hat Openshift

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Author : Ross Brigoli
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-01-31

Mlops With Red Hat Openshift written by Ross Brigoli and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-31 with Computers categories.

Build and manage MLOps pipelines with this practical guide to using Red Hat OpenShift Data Science, unleashing the power of machine learning workflows Key Features Grasp MLOps and machine learning project lifecycle through concept introductions Get hands on with provisioning and configuring Red Hat OpenShift Data Science Explore model training, deployment, and MLOps pipeline building with step-by-step instructions Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionMLOps with OpenShift offers practical insights for implementing MLOps workflows on the dynamic OpenShift platform. As organizations worldwide seek to harness the power of machine learning operations, this book lays the foundation for your MLOps success. Starting with an exploration of key MLOps concepts, including data preparation, model training, and deployment, you’ll prepare to unleash OpenShift capabilities, kicking off with a primer on containers, pods, operators, and more. With the groundwork in place, you’ll be guided to MLOps workflows, uncovering the applications of popular machine learning frameworks for training and testing models on the platform. As you advance through the chapters, you’ll focus on the open-source data science and machine learning platform, Red Hat OpenShift Data Science, and its partner components, such as Pachyderm and Intel OpenVino, to understand their role in building and managing data pipelines, as well as deploying and monitoring machine learning models. Armed with this comprehensive knowledge, you’ll be able to implement MLOps workflows on the OpenShift platform proficiently.What you will learn Build a solid foundation in key MLOps concepts and best practices Explore MLOps workflows, covering model development and training Implement complete MLOps workflows on the Red Hat OpenShift platform Build MLOps pipelines for automating model training and deployments Discover model serving approaches using Seldon and Intel OpenVino Get to grips with operating data science and machine learning workloads in OpenShift Who this book is for This book is for MLOps and DevOps engineers, data architects, and data scientists interested in learning the OpenShift platform. Particularly, developers who want to learn MLOps and its components will find this book useful. Whether you’re a machine learning engineer or software developer, this book serves as an essential guide to building scalable and efficient machine learning workflows on the OpenShift platform.

Machine Learning Engineering On Aws

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Author : Joshua Arvin Lat
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-10-27

Machine Learning Engineering On Aws written by Joshua Arvin Lat and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-27 with Computers categories.

Work seamlessly with production-ready machine learning systems and pipelines on AWS by addressing key pain points encountered in the ML life cycle Key FeaturesGain practical knowledge of managing ML workloads on AWS using Amazon SageMaker, Amazon EKS, and moreUse container and serverless services to solve a variety of ML engineering requirementsDesign, build, and secure automated MLOps pipelines and workflows on AWSBook Description There is a growing need for professionals with experience in working on machine learning (ML) engineering requirements as well as those with knowledge of automating complex MLOps pipelines in the cloud. This book explores a variety of AWS services, such as Amazon Elastic Kubernetes Service, AWS Glue, AWS Lambda, Amazon Redshift, and AWS Lake Formation, which ML practitioners can leverage to meet various data engineering and ML engineering requirements in production. This machine learning book covers the essential concepts as well as step-by-step instructions that are designed to help you get a solid understanding of how to manage and secure ML workloads in the cloud. As you progress through the chapters, you'll discover how to use several container and serverless solutions when training and deploying TensorFlow and PyTorch deep learning models on AWS. You'll also delve into proven cost optimization techniques as well as data privacy and model privacy preservation strategies in detail as you explore best practices when using each AWS. By the end of this AWS book, you'll be able to build, scale, and secure your own ML systems and pipelines, which will give you the experience and confidence needed to architect custom solutions using a variety of AWS services for ML engineering requirements. What you will learnFind out how to train and deploy TensorFlow and PyTorch models on AWSUse containers and serverless services for ML engineering requirementsDiscover how to set up a serverless data warehouse and data lake on AWSBuild automated end-to-end MLOps pipelines using a variety of servicesUse AWS Glue DataBrew and SageMaker Data Wrangler for data engineeringExplore different solutions for deploying deep learning models on AWSApply cost optimization techniques to ML environments and systemsPreserve data privacy and model privacy using a variety of techniquesWho this book is for This book is for machine learning engineers, data scientists, and AWS cloud engineers interested in working on production data engineering, machine learning engineering, and MLOps requirements using a variety of AWS services such as Amazon EC2, Amazon Elastic Kubernetes Service (EKS), Amazon SageMaker, AWS Glue, Amazon Redshift, AWS Lake Formation, and AWS Lambda -- all you need is an AWS account to get started. Prior knowledge of AWS, machine learning, and the Python programming language will help you to grasp the concepts covered in this book more effectively.

Applied Machine Learning And High Performance Computing On Aws

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Author : Mani Khanuja
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-12-30

Applied Machine Learning And High Performance Computing On Aws written by Mani Khanuja and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-30 with Computers categories.

Build, train, and deploy large machine learning models at scale in various domains such as computational fluid dynamics, genomics, autonomous vehicles, and numerical optimization using Amazon SageMaker Key FeaturesUnderstand the need for high-performance computing (HPC)Build, train, and deploy large ML models with billions of parameters using Amazon SageMakerLearn best practices and architectures for implementing ML at scale using HPCBook Description Machine learning (ML) and high-performance computing (HPC) on AWS run compute-intensive workloads across industries and emerging applications. Its use cases can be linked to various verticals, such as computational fluid dynamics (CFD), genomics, and autonomous vehicles. This book provides end-to-end guidance, starting with HPC concepts for storage and networking. It then progresses to working examples on how to process large datasets using SageMaker Studio and EMR. Next, you'll learn how to build, train, and deploy large models using distributed training. Later chapters also guide you through deploying models to edge devices using SageMaker and IoT Greengrass, and performance optimization of ML models, for low latency use cases. By the end of this book, you'll be able to build, train, and deploy your own large-scale ML application, using HPC on AWS, following industry best practices and addressing the key pain points encountered in the application life cycle. What you will learnExplore data management, storage, and fast networking for HPC applicationsFocus on the analysis and visualization of a large volume of data using SparkTrain visual transformer models using SageMaker distributed trainingDeploy and manage ML models at scale on the cloud and at the edgeGet to grips with performance optimization of ML models for low latency workloadsApply HPC to industry domains such as CFD, genomics, AV, and optimizationWho this book is for The book begins with HPC concepts, however, it expects you to have prior machine learning knowledge. This book is for ML engineers and data scientists interested in learning advanced topics on using large datasets for training large models using distributed training concepts on AWS, deploying models at scale, and performance optimization for low latency use cases. Practitioners in fields such as numerical optimization, computation fluid dynamics, autonomous vehicles, and genomics, who require HPC for applying ML models to applications at scale will also find the book useful.

Aws Certified Sysops Administrator Associate Soa C01 Cert Guide

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Author : Anthony J. Sequeira
language : en
Publisher: Pearson IT Certification
Release Date : 2019-11-26

Aws Certified Sysops Administrator Associate Soa C01 Cert Guide written by Anthony J. Sequeira and has been published by Pearson IT Certification this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-26 with Computers categories.

This is the eBook version of the print title. Note that the eBook does not provide access to the practice test software that accompanies the print book. Learn, prepare, and practice for AWS Certified SysOps Administrator Associate (SOA-C01) exam success with this Cert Guide from Pearson IT Certification, a leader in IT Certification learning. Master AWS Certified SysOps Administrator Associate (SOA-C01) exam topics Assess your knowledge with chapter-ending quizzes Review key concepts with exam preparation tasks AWS Certified SysOps Administrator Associate (SOA-C01) Cert Guide is a best-of-breed exam study guide. Best-selling author and expert instructor Anthony Sequeira shares preparation hints and test-taking tips, helping you identify areas of weakness and improve both your conceptual knowledge and hands-on skills. Material is presented in a concise manner, focusing on increasing your understanding and retention of exam topics. The book presents you with an organized test preparation routine through the use of proven series elements and techniques. Exam topic lists make referencing easy. Chapter-ending Exam Preparation Tasks help you drill on key concepts you must know thoroughly. Review questions help you assess your knowledge, and a final preparation chapter guides you through tools and resources to help you craft your final study plan. Well-regarded for its level of detail, assessment features, and challenging review questions and exercises, this study guide helps you master the concepts and techniques that will enable you to succeed on the exam the first time. The study guide helps you master all the topics on the AWS Certified SysOps Administrator Associate exam, including: Monitoring and reporting: create and maintain metrics and alarms; recognize, differentiate, and remediate based on metrics High availability: implement scalability and elasticity; recognize and differentiate highly available and resilient AWS environments Deployment and provisioning: provision cloud resources, and identify and remediate deployment issues Storage and data management: create and manage data retention; identify and implement data protection, encryption, and capacity planning Security and compliance: implement and manage security policies; implement access controls; understand the shared responsibility model Networking: use AWS networking features and connectivity services; gather and interpret relevant data for network troubleshooting Automation and optimization: manage and assess resource utilization, use cost-optimization strategies, and automate processes

Ultimate Aws Certified Solutions Architect Professional Exam Sapc02 Guide

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Author : Gaurav H Kankaria
language : en
Publisher: Orange Education Pvt Ltd
Release Date : 2025-02-15

Ultimate Aws Certified Solutions Architect Professional Exam Sapc02 Guide written by Gaurav H Kankaria and has been published by Orange Education Pvt Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-15 with Computers categories.

TAGLINE Pass the AWS Solutions Architect Pro Exam with Confidence. KEY FEATURES ● Dive deep into all critical areas of the exam, including advanced architecture, cost optimization, high availability, and security. ● Engage with interactive exercises that simulate real-world cloud challenges. ● Learn from experienced professionals who share insider tips, proven strategies, and common pitfalls to avoid. DESCRIPTION The AWS Certified Solutions Architect Professional certification is a vital credential for IT professionals seeking to advance their careers in cloud architecture. Mastering the complexities of AWS requires a deep understanding of its architecture and services. The Ultimate AWS Certified Solutions Architect Professional Exam Guide is your comprehensive resource to conquering the AWS Certified Solutions Architect Professional exam. It is designed to equip you with the knowledge and practical skills necessary to design and deploy scalable, high-performing, and cost-effective cloud solutions. Delve into core AWS services, advanced architecture patterns, and best practices. Explore topics such as VPC design, security, high availability, cost optimization, and more. Each chapter offers in-depth explanations, real-world examples, and exercises to solidify your understanding. By the end of this book, you will be confident in architecting robust cloud solutions, troubleshooting complex issues, and successfully passing the AWS Certified Solutions Architect Professional exam. With a solid grasp of AWS architecture and a proven exam preparation strategy, you will be well-prepared to excel as a cloud architect and drive innovation within your organization. WHAT WILL YOU LEARN ● Design scalable, secure, and cost-effective cloud architectures on AWS. ● Master VPC design, security, and implement high-availability best practices. ● Optimize AWS services for peak performance, reliability, and cost efficiency. ● Troubleshoot complex cloud infrastructure issues with precision and confidence. ● Prepare effectively for the AWS Solution Architect Professional certification exam. ● Gain practical experience through real-world scenarios and hands-on exercises. WHO IS THIS BOOK FOR? This book is tailored for IT professionals aiming for the AWS Certified Solutions Architect Professional certification. It is also ideal for experienced Solution Architects looking to enhance their expertise and for those working in cloud computing roles who need a deep understanding of AWS architecture and best practices. TABLE OF CONTENTS 1. Introduction to AWS Solution Architect Professional Exam 2. Advanced Architecting on AWS 3. Security Practices in AWS 4. High Availability and Disaster Recovery 5. Performance Optimization and Scalability 6. Cost Optimization 7. Migration and Modernization 8. DevOps and Continuous Delivery 9. Advanced Networking and Content Delivery 10. Big Data and Analytics 11. Serverless Computing and Microservices 12. Emerging Technologies and Trends 13. Preparing for Exam Index

Serverless Machine Learning With Amazon Redshift Ml

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