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Python And Aws Cookbook
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Book Synopsis Python and AWS Cookbook by : Mitch Garnaat
Download or read book Python and AWS Cookbook written by Mitch Garnaat and published by "O'Reilly Media, Inc.". This book was released on 2011-10-24 with total page 75 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you intend to use Amazon Web Services (AWS) for remote computing and storage, Python is an ideal programming language for developing applications and controlling your cloud-based infrastructure. This cookbook gets you started with more than two dozen recipes for using Python with AWS, based on the author’s boto library. You’ll find detailed recipes for working with the S3 storage service as well as EC2, the service that lets you design and build cloud applications. Each recipe includes a code solution you can use immediately, along with a discussion of why and how the recipe works. You also get detailed advice for using boto with AWS and other cloud services. This book’s recipes include methods to help you: Launch instances on EC2, and keep track of them with tags Associate an Elastic IP address with an instance Restore a failed Elastic Block Store volume from a snapshot Store and monitor your own custom metrics in CloudWatch Create a bucket in S3 to contain your data objects Reduce the cost of storing noncritical data Prevent accidental deletion of data in S3
Book Synopsis Python and AWS Cookbook by : Mitch Garnaat
Download or read book Python and AWS Cookbook written by Mitch Garnaat and published by "O'Reilly Media, Inc.". This book was released on 2011-10-24 with total page 75 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you intend to use Amazon Web Services (AWS) for remote computing and storage, Python is an ideal programming language for developing applications and controlling your cloud-based infrastructure. This cookbook gets you started with more than two dozen recipes for using Python with AWS, based on the author’s boto library. You’ll find detailed recipes for working with the S3 storage service as well as EC2, the service that lets you design and build cloud applications. Each recipe includes a code solution you can use immediately, along with a discussion of why and how the recipe works. You also get detailed advice for using boto with AWS and other cloud services. This book’s recipes include methods to help you: Launch instances on EC2, and keep track of them with tags Associate an Elastic IP address with an instance Restore a failed Elastic Block Store volume from a snapshot Store and monitor your own custom metrics in CloudWatch Create a bucket in S3 to contain your data objects Reduce the cost of storing noncritical data Prevent accidental deletion of data in S3
Download or read book AWS Cookbook written by John Culkin and published by "O'Reilly Media, Inc.". This book was released on 2021-12-02 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: This practical guide provides over 70 self-contained recipes to help you creatively solve common AWS challenges you'll encounter on your cloud journey. If you're comfortable with rudimentary scripting and general cloud concepts, this cookbook provides what you need to address foundational tasks and create high-level capabilities. Authors John Culkin and Mike Zazon share real-world examples that incorporate best practices. Each recipe includes a diagram to visualize the components. Code is provided so that you can safely execute in an AWS account to ensure solutions work as described. From there, you can customize the code to help construct an application or fix an existing problem. Each recipe also includes a discussion to provide context, explain the approach, and challenge you to explore the possibilities further. Go beyond theory and learn the details you need to successfully build on AWS. The recipes help you: Redact personal identifiable information (PII) from text using Amazon Comprehend Automate password rotation for Amazon RDS databases Use VPC Reachability Analyzer to verify and troubleshoot network paths Lock down Amazon Simple Storage Service (S3) buckets Analyze AWS Identity and Access Management policies Autoscale a containerized service
Book Synopsis AWS System Administration by : Mike Ryan
Download or read book AWS System Administration written by Mike Ryan and published by "O'Reilly Media, Inc.". This book was released on 2018-08-08 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: With platforms designed for rapid adaptation and failure recovery such as Amazon Web Services, cloud computing is more like programming than traditional system administration. Tools for automatic scaling and instance replacement allow even small DevOps teams to manage massively scalable application infrastructures—if team members drop their old views of development and operations and start mastering automation. This comprehensive guide shows developers and system administrators how to configure and manage AWS services including EC2, CloudFormation, Elastic Load Balancing, S3, and Route 53. Sysadms will learn will learn to automate their favorite tools and processes; developers will pick up enough ops knowledge to build a robust and resilient AWS application infrastructure. Launch instances with EC2 or CloudFormation Securely deploy and manage your applications with AWS tools Learn to automate AWS configuration management with Python and Puppet Deploy applications with Auto Scaling and Elastic Load Balancing Explore approaches for deploying application and infrastructure updates Save time on development and operations with reusable components Learn strategies for managing log files in AWS environments Configure a cloud-aware DNS service with Route 53 Use AWS CloudWatch to monitor your infrastructure and applications
Book Synopsis Resilience and Reliability on AWS by : Jurg van Vliet
Download or read book Resilience and Reliability on AWS written by Jurg van Vliet and published by "O'Reilly Media, Inc.". This book was released on 2013-01-03 with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cloud services are just as susceptible to network outages as any other platform. This concise book shows you how to prepare for potentially devastating interruptions by building your own resilient and reliable applications in the public cloud. Guided by engineers from 9apps—an independent provider of Amazon Web Services and Eucalyptus cloud solutions—you’ll learn how to combine AWS with open source tools such as PostgreSQL, MongoDB, and Redis. This isn’t a book on theory. With detailed examples, sample scripts, and solid advice, software engineers with operations experience will learn specific techniques that 9apps routinely uses in its cloud infrastructures. Build cloud applications with the "rip, mix, and burn" approach Get a crash course on Amazon Web Services Learn the top ten tips for surviving outages in the cloud Use elasticsearch to build a dependable NoSQL data store Combine AWS and PostgreSQL to build an RDBMS that scales well Create a highly available document database with MongoDB Replica Set and SimpleDB Augment Redis with AWS to provide backup/restore, failover, and monitoring capabilities Work with CloudFront and Route 53 to safeguard global content delivery
Book Synopsis Web Scraping with Python by : Ryan Mitchell
Download or read book Web Scraping with Python written by Ryan Mitchell and published by "O'Reilly Media, Inc.". This book was released on 2015-06-15 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn web scraping and crawling techniques to access data from any web source in any format. Teaches basic web scraping mechanics, but also delves into more advanced topics, such as analyzing raw data or using scrapers for frontend website testing.
Book Synopsis AWS Security Cookbook by : Heartin Kanikathottu
Download or read book AWS Security Cookbook written by Heartin Kanikathottu and published by Packt Publishing Ltd. This book was released on 2020-02-27 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: Secure your Amazon Web Services (AWS) infrastructure with permission policies, key management, and network security, along with following cloud security best practices Key FeaturesExplore useful recipes for implementing robust cloud security solutions on AWSMonitor your AWS infrastructure and workloads using CloudWatch, CloudTrail, config, GuardDuty, and MaciePrepare for the AWS Certified Security-Specialty exam by exploring various security models and compliance offeringsBook Description As a security consultant, securing your infrastructure by implementing policies and following best practices is critical. This cookbook discusses practical solutions to the most common problems related to safeguarding infrastructure, covering services and features within AWS that can help you implement security models such as the CIA triad (confidentiality, integrity, and availability), and the AAA triad (authentication, authorization, and availability), along with non-repudiation. The book begins with IAM and S3 policies and later gets you up to speed with data security, application security, monitoring, and compliance. This includes everything from using firewalls and load balancers to secure endpoints, to leveraging Cognito for managing users and authentication. Over the course of this book, you'll learn to use AWS security services such as Config for monitoring, as well as maintain compliance with GuardDuty, Macie, and Inspector. Finally, the book covers cloud security best practices and demonstrates how you can integrate additional security services such as Glacier Vault Lock and Security Hub to further strengthen your infrastructure. By the end of this book, you'll be well versed in the techniques required for securing AWS deployments, along with having the knowledge to prepare for the AWS Certified Security – Specialty certification. What you will learnCreate and manage users, groups, roles, and policies across accountsUse AWS Managed Services for logging, monitoring, and auditingCheck compliance with AWS Managed Services that use machine learningProvide security and availability for EC2 instances and applicationsSecure data using symmetric and asymmetric encryptionManage user pools and identity pools with federated loginWho this book is for If you are an IT security professional, cloud security architect, or a cloud application developer working on security-related roles and are interested in using AWS infrastructure for secure application deployments, then this Amazon Web Services book is for you. You will also find this book useful if you’re looking to achieve AWS certification. Prior knowledge of AWS and cloud computing is required to get the most out of this book.
Book Synopsis Amazon Redshift Cookbook by : Shruti Worlikar
Download or read book Amazon Redshift Cookbook written by Shruti Worlikar and published by Packt Publishing Ltd. This book was released on 2021-07-23 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover how to build a cloud-based data warehouse at petabyte-scale that is burstable and built to scale for end-to-end analytical solutions Key FeaturesDiscover how to translate familiar data warehousing concepts into Redshift implementationUse impressive Redshift features to optimize development, productionizing, and operations processesFind out how to use advanced features such as concurrency scaling, Redshift Spectrum, and federated queriesBook Description Amazon Redshift is a fully managed, petabyte-scale AWS cloud data warehousing service. It enables you to build new data warehouse workloads on AWS and migrate on-premises traditional data warehousing platforms to Redshift. This book on Amazon Redshift starts by focusing on Redshift architecture, showing you how to perform database administration tasks on Redshift. You'll then learn how to optimize your data warehouse to quickly execute complex analytic queries against very large datasets. Because of the massive amount of data involved in data warehousing, designing your database for analytical processing lets you take full advantage of Redshift's columnar architecture and managed services. As you advance, you'll discover how to deploy fully automated and highly scalable extract, transform, and load (ETL) processes, which help minimize the operational efforts that you have to invest in managing regular ETL pipelines and ensure the timely and accurate refreshing of your data warehouse. Finally, you'll gain a clear understanding of Redshift use cases, data ingestion, data management, security, and scaling so that you can build a scalable data warehouse platform. By the end of this Redshift book, you'll be able to implement a Redshift-based data analytics solution and have understood the best practice solutions to commonly faced problems. What you will learnUse Amazon Redshift to build petabyte-scale data warehouses that are agile at scaleIntegrate your data warehousing solution with a data lake using purpose-built features and services on AWSBuild end-to-end analytical solutions from data sourcing to consumption with the help of useful recipesLeverage Redshift's comprehensive security capabilities to meet the most demanding business requirementsFocus on architectural insights and rationale when using analytical recipesDiscover best practices for working with big data to operate a fully managed solutionWho this book is for This book is for anyone involved in architecting, implementing, and optimizing an Amazon Redshift data warehouse, such as data warehouse developers, data analysts, database administrators, data engineers, and data scientists. Basic knowledge of data warehousing, database systems, and cloud concepts and familiarity with Redshift will be beneficial.
Book Synopsis Machine Learning with Amazon SageMaker Cookbook by : Joshua Arvin Lat
Download or read book Machine Learning with Amazon SageMaker Cookbook written by Joshua Arvin Lat and published by Packt Publishing Ltd. This book was released on 2021-10-29 with total page 763 pages. Available in PDF, EPUB and Kindle. Book excerpt: A step-by-step solution-based guide to preparing building, training, and deploying high-quality machine learning models with Amazon SageMaker Key FeaturesPerform ML experiments with built-in and custom algorithms in SageMakerExplore proven solutions when working with TensorFlow, PyTorch, Hugging Face Transformers, and scikit-learnUse the different features and capabilities of SageMaker to automate relevant ML processesBook Description Amazon SageMaker is a fully managed machine learning (ML) service that helps data scientists and ML practitioners manage ML experiments. In this book, you'll use the different capabilities and features of Amazon SageMaker to solve relevant data science and ML problems. This step-by-step guide features 80 proven recipes designed to give you the hands-on machine learning experience needed to contribute to real-world experiments and projects. You'll cover the algorithms and techniques that are commonly used when training and deploying NLP, time series forecasting, and computer vision models to solve ML problems. You'll explore various solutions for working with deep learning libraries and frameworks such as TensorFlow, PyTorch, and Hugging Face Transformers in Amazon SageMaker. You'll also learn how to use SageMaker Clarify, SageMaker Model Monitor, SageMaker Debugger, and SageMaker Experiments to debug, manage, and monitor multiple ML experiments and deployments. Moreover, you'll have a better understanding of how SageMaker Feature Store, Autopilot, and Pipelines can meet the specific needs of data science teams. By the end of this book, you'll be able to combine the different solutions you've learned as building blocks to solve real-world ML problems. What you will learnTrain and deploy NLP, time series forecasting, and computer vision models to solve different business problemsPush the limits of customization in SageMaker using custom container imagesUse AutoML capabilities with SageMaker Autopilot to create high-quality modelsWork with effective data analysis and preparation techniquesExplore solutions for debugging and managing ML experiments and deploymentsDeal with bias detection and ML explainability requirements using SageMaker ClarifyAutomate intermediate and complex deployments and workflows using a variety of solutionsWho this book is for This book is for developers, data scientists, and machine learning practitioners interested in using Amazon SageMaker to build, analyze, and deploy machine learning models with 80 step-by-step recipes. All you need is an AWS account to get things running. Prior knowledge of AWS, machine learning, and the Python programming language will help you to grasp the concepts covered in this book more effectively.
Book Synopsis Building Serverless Applications with Python by : Jalem Raj Rohit
Download or read book Building Serverless Applications with Python written by Jalem Raj Rohit and published by Packt Publishing Ltd. This book was released on 2018-04-20 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Building efficient Python applications at minimal cost by adopting serverless architectures Key Features Design and set up a data flow between cloud services and custom business logic Make your applications efficient and reliable using serverless architecture Build and deploy scalable serverless Python APIs Book Description Serverless architectures allow you to build and run applications and services without having to manage the infrastructure. Many companies have adopted this architecture to save cost and improve scalability. This book will help you design serverless architectures for your applications with AWS and Python. The book is divided into three modules. The first module explains the fundamentals of serverless architecture and how AWS lambda functions work. In the next module, you will learn to build, release, and deploy your application to production. You will also learn to log and test your application. In the third module, we will take you through advanced topics such as building a serverless API for your application. You will also learn to troubleshoot and monitor your app and master AWS lambda programming concepts with API references. Moving on, you will also learn how to scale up serverless applications and handle distributed serverless systems in production. By the end of the book, you will be equipped with the knowledge required to build scalable and cost-efficient Python applications with a serverless framework. What you will learn Understand how AWS Lambda and Microsoft Azure Functions work and use them to create an application Explore various triggers and how to select them, based on the problem statement Build deployment packages for Lambda functions Master the finer details about building Lambda functions and versioning Log and monitor serverless applications Learn about security in AWS and Lambda functions Scale up serverless applications to handle huge workloads and serverless distributed systems in production Understand SAM model deployment in AWS Lambda Who this book is for This book is for Python developers who would like to learn about serverless architecture. Python programming knowledge is assumed.
Book Synopsis Network Automation Cookbook by : Karim Okasha
Download or read book Network Automation Cookbook written by Karim Okasha and published by Packt Publishing Ltd. This book was released on 2020-04-17 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: Take your network automation skills to the next level with practical recipes on managing network devices from a variety of vendors like Cisco, Juniper, and Arista Key FeaturesUse Ansible to automate network infrastructure with the help of step-by-step instructionsImplement network automation best practices to save cost, avoid critical errors, and reduce downtimeDeliver a robust automation framework by integrating Ansible with NAPALM, NetBox, and BatfishBook Description Network Automation Cookbook is designed to help system administrators, network engineers, and infrastructure automation engineers to centrally manage switches, routers, and other devices in their organization's network. This book will help you gain hands-on experience in automating enterprise networks and take you through core network automation techniques using the latest version of Ansible and Python. With the help of practical recipes, you'll learn how to build a network infrastructure that can be easily managed and updated as it scales through a large number of devices. You'll also cover topics related to security automation and get to grips with essential techniques to maintain network robustness. As you make progress, the book will show you how to automate networks on public cloud providers such as AWS, Google Cloud Platform, and Azure. Finally, you will get up and running with Ansible 2.9 and discover troubleshooting techniques and network automation best practices. By the end of this book, you'll be able to use Ansible to automate modern network devices and integrate third-party tools such as NAPALM, NetBox, and Batfish easily to build robust network automation solutions. What you will learnUnderstand the various components of AnsibleAutomate network resources in AWS, GCP, and Azure cloud solutionsUse IaC concepts to design and build network solutionsAutomate network devices such as Cisco, Juniper, Arista, and F5Use NetBox to build network inventory and integrate it with AnsibleValidate networks using Ansible and BatfishWho this book is for This Ansible network automation book is for network and DevOps engineers interested in automating complex network tasks. Prior understanding of networking and basic Linux knowledge is required.
Book Synopsis Ansible 2 Cloud Automation Cookbook by : Aditya Patawari
Download or read book Ansible 2 Cloud Automation Cookbook written by Aditya Patawari and published by Packt Publishing Ltd. This book was released on 2018-02-28 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: Orchestrate your cloud infrastructure Key Features Recipe-based approach to install and configure cloud resources using Ansible Covers various cloud-related modules and their functionalities Includes deployment of a sample application to the cloud resources that we create Learn the best possible way to manage and automate your cloud infrastructure Book Description Ansible has a large collection of inbuilt modules to manage various cloud resources. The book begins with the concepts needed to safeguard your credentials and explain how you interact with cloud providers to manage resources. Each chapter begins with an introduction and prerequisites to use the right modules to manage a given cloud provider. Learn about Amazon Web Services, Google Cloud, Microsoft Azure, and other providers. Each chapter shows you how to create basic computing resources, which you can then use to deploy an application. Finally, you will be able to deploy a sample application to demonstrate various usage patterns and utilities of resources. What you will learn Use Ansible Vault to protect secrets Understand how Ansible modules interact with cloud providers to manage resources Build cloud-based resources for your application Create resources beyond simple virtual machines Write tasks that can be reused to create resources multiple times Work with self-hosted clouds such as OpenStack and Docker Deploy a multi-tier application on various cloud providers Who this book is for If you are a system administrator, infrastructure engineer, or a DevOps engineer who wants to obtain practical knowledge about Ansible and its cloud deliverables, then this book is for you. Recipes in this book are designed for people who would like to manage their cloud infrastructures efficiently using Ansible, which is regarded as one of the best tools for cloud management and automation.
Book Synopsis Databricks Lakehouse Platform Cookbook by : Dr. Alan L. Dennis
Download or read book Databricks Lakehouse Platform Cookbook written by Dr. Alan L. Dennis and published by BPB Publications. This book was released on 2023-12-18 with total page 610 pages. Available in PDF, EPUB and Kindle. Book excerpt: Analyze, Architect, and Innovate with Databricks Lakehouse KEY FEATURES ● Create a Lakehouse using Databricks, including ingestion from source to Bronze. ● Refinement of Bronze items to business-ready Silver items using incremental methods. ● Construct Gold items to service the needs of various business requirements. DESCRIPTION The Databricks Lakehouse is groundbreaking technology that simplifies data storage, processing, and analysis. This cookbook offers a clear and practical guide to building and optimizing your Lakehouse to make data-driven decisions and drive impactful results. This definitive guide walks you through the entire Lakehouse journey, from setting up your environment, and connecting to storage, to creating Delta tables, building data models, and ingesting and transforming data. We start off by discussing how to ingest data to Bronze, then refine it to produce Silver. Next, we discuss how to create Gold tables and various data modeling techniques often performed in the Gold layer. You will learn how to leverage Spark SQL and PySpark for efficient data manipulation, apply Delta Live Tables for real-time data processing, and implement Machine Learning and Data Science workflows with MLflow, Feature Store, and AutoML. The book also delves into advanced topics like graph analysis, data governance, and visualization, equipping you with the necessary knowledge to solve complex data challenges. By the end of this cookbook, you will be a confident Lakehouse expert, capable of designing, building, and managing robust data-driven solutions. WHAT YOU WILL LEARN ● Design and build a robust Databricks Lakehouse environment. ● Create and manage Delta tables with advanced transformations. ● Analyze and transform data using SQL and Python. ● Build and deploy machine learning models for actionable insights. ● Implement best practices for data governance and security. WHO THIS BOOK IS FOR This book is meant for Data Engineers, Data Analysts, Data Scientists, Business intelligence professionals, and Architects who want to go to the next level of Data Engineering using the Databricks platform to construct Lakehouses. TABLE OF CONTENTS 1. Introduction to Databricks Lakehouse 2. Setting Up a Databricks Workspace 3. Connecting to Storage 4. Creating Delta Tables 5. Data Profiling and Modeling in the Lakehouse 6. Extracting from Source and Loading to Bronze 7. Transforming to Create Silver 8. Transforming to Create Gold for Business Purposes 9. Machine Learning and Data Science 10. SQL Analysis 11. Graph Analysis 12. Visualizations 13. Governance 14. Operations 15. Tips, Tricks, Troubleshooting, and Best Practices
Book Synopsis Flask Framework Cookbook by : Shalabh Aggarwal
Download or read book Flask Framework Cookbook written by Shalabh Aggarwal and published by Packt Publishing Ltd. This book was released on 2019-07-17 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build state-of-the-art web applications quickly and efficiently using Flask and related technologies with Python 3 Key FeaturesUpdated to Flask 1.0.3 and Python 3.7 with coverage of MicroservicesGet the most out of the powerful Flask framework and maintain the flexibility of your design choicesWrite cleaner and maintainable code with the help of sample appsBook Description Flask, the lightweight Python web framework, is popular due to its powerful modular design that lets you build scalable web apps. With this recipe-based guide, you’ll explore modern solutions and best practices for Flask web development. Updated to the latest version of Flask and Python 3, this second edition of Flask Framework Cookbook moves away from some of the old and obsolete libraries and introduces recipes on bleeding edge technologies. You’ll discover different ways of using Flask to create, deploy, and manage microservices. This Flask Python book starts by covering the different configurations that a Flask application can make use of, and then helps you work with templates and learn about the ORM and view layers. You’ll also be able to write an admin interface and get to grips with debugging and logging errors. Finally, you’ll grasp a variety of deployment and post-deployment techniques for platforms such as Apache, Tornado, and Heroku. By the end of this book, you’ll have gained all the knowledge you need to write Flask applications in the best possible way and scale them using standard industry practices. What you will learnExplore web application development in Flask, right from installation to post-deployment stagesMake use of advanced templating and data modeling techniquesDiscover effective debugging, logging, and error handling techniques in FlaskIntegrate Flask with different technologies such as Redis, Sentry, and MongoDBDeploy and package Flask applications with Docker and KubernetesDesign scalable microservice architecture using AWS LambdaContinuous integration and Continuous deploymentWho this book is for If you are a web developer who wants to learn more about developing scalable and production-ready applications in Flask, this is the book for you. You’ll also find this book useful if you are already aware of Flask's major extensions and want to use them for better application development. Basic Python programming experience along with basic understanding of Flask is assumed.
Book Synopsis Machine Learning Engineering on AWS by : Joshua Arvin Lat
Download or read book Machine Learning Engineering on AWS written by Joshua Arvin Lat and published by Packt Publishing Ltd. This book was released on 2022-10-27 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Computer Vision on AWS by : Lauren Mullennex
Download or read book Computer Vision on AWS written by Lauren Mullennex and published by Packt Publishing Ltd. This book was released on 2023-03-31 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: Develop scalable computer vision solutions for real-world business problems and discover scaling, cost reduction, security, and bias mitigation best practices with AWS AI/ML services Purchase of the print or Kindle book includes a free PDF eBook Key Features Learn how to quickly deploy and automate end-to-end CV pipelines on AWS Implement design principles to mitigate bias and scale production of CV workloads Work with code examples to master CV concepts using AWS AI/ML services Book Description Computer vision (CV) is a field of artificial intelligence that helps transform visual data into actionable insights to solve a wide range of business challenges. This book provides prescriptive guidance to anyone looking to learn how to approach CV problems for quickly building and deploying production-ready models. You'll begin by exploring the applications of CV and the features of Amazon Rekognition and Amazon Lookout for Vision. The book will then walk you through real-world use cases such as identity verification, real-time video analysis, content moderation, and detecting manufacturing defects that'll enable you to understand how to implement AWS AI/ML services. As you make progress, you'll also use Amazon SageMaker for data annotation, training, and deploying CV models. In the concluding chapters, you'll work with practical code examples, and discover best practices and design principles for scaling, reducing cost, improving the security posture, and mitigating bias of CV workloads. By the end of this AWS book, you'll be able to accelerate your business outcomes by building and implementing CV into your production environments with the help of AWS AI/ML services. What you will learn Apply CV across industries, including e-commerce, logistics, and media Build custom image classifiers with Amazon Rekognition Custom Labels Create automated end-to-end CV workflows on AWS Detect product defects on edge devices using Amazon Lookout for Vision Build, deploy, and monitor CV models using Amazon SageMaker Discover best practices for designing and evaluating CV workloads Develop an AI governance strategy across the entire machine learning life cycle Who this book is for If you are a machine learning engineer or data scientist looking to discover best practices and learn how to build comprehensive CV solutions on AWS, this book is for you. Knowledge of AWS basics is required to grasp the concepts covered in this book more effectively. A solid understanding of machine learning concepts and the Python programming language will also be beneficial.
