Prepare to achieve AWS Machine Learning Specialty certification with this complete, up-to-date guide and take the exam with confidence Key Features Get to grips with core machine learning algorithms along with AWS implementation Build model training and inference pipelines and deploy machine learning models to the Amazon Web Services (AWS) cloud Learn all about the AWS services available for machine learning in order to pass the MLS-C01 exam Book DescriptionThe AWS Certified Machine Learning Specialty exam tests your competency to perform machine learning (ML) on AWS infrastructure. This book covers the entire exam syllabus using practical examples to help you with your real-world machine learning projects on AWS. Starting with an introduction to machine learning on AWS, you'll learn the fundamentals of machine learning and explore important AWS services for artificial intelligence (AI). You'll then see how to prepare data for machine learning and discover a wide variety of techniques for data manipulation and transformation for different types of variables. The book also shows you how to handle missing data and outliers and takes you through various machine learning tasks such as classification, regression, clustering, forecasting, anomaly detection, text mining, and image processing, along with the specific ML algorithms you need to know to pass the exam. Finally, you'll explore model evaluation, optimization, and deployment and get to grips with deploying models in a production environment and monitoring them. By the end of this book, you'll have gained knowledge of the key challenges in machine learning and the solutions that AWS has released for each of them, along with the tools, methods, and techniques commonly used in each domain of AWS ML. What you will learn Understand all four domains covered in the exam, along with types of questions, exam duration, and scoring Become well-versed with machine learning terminologies, methodologies, frameworks, and the different AWS services for machine learning Get to grips with data preparation and using AWS services for batch and real-time data processing Explore the built-in machine learning algorithms in AWS and build and deploy your own models Evaluate machine learning models and tune hyperparameters Deploy machine learning models with the AWS infrastructure Who this book is forThis AWS book is for professionals and students who want to prepare for and pass the AWS Certified Machine Learning Specialty exam or gain deeper knowledge of machine learning with a special focus on AWS. Beginner-level knowledge of machine learning and AWS services is necessary before getting started with this book.

Apply cloud design patterns to overcome real-world challenges by building scalable, secure, highly available, and cost-effective solutions Key Features Apply AWS Well-Architected Framework concepts to common real-world use cases Understand how to select AWS patterns and architectures that are best suited to your needs Ensure the security and stability of a solution without impacting cost or performance Book DescriptionOne of the most popular cloud platforms in the world, Amazon Web Services (AWS) offers hundreds of services with thousands of features to help you build scalable cloud solutions; however, it can be overwhelming to navigate the vast number of services and decide which ones best suit your requirements. Whether you are an application architect, enterprise architect, developer, or operations engineer, this book will take you through AWS architectural patterns and guide you in selecting the most appropriate services for your projects. AWS for Solutions Architects is a comprehensive guide that covers the essential concepts that you need to know for designing well-architected AWS solutions that solve the challenges organizations face daily. You'll get to grips with AWS architectural principles and patterns by implementing best practices and recommended techniques for real-world use cases. The book will show you how to enhance operational efficiency, security, reliability, performance, and cost-effectiveness using real-world examples. By the end of this AWS book, you'll have gained a clear understanding of how to design AWS architectures using the most appropriate services to meet your organization's technological and business requirements. What you will learn Rationalize the selection of AWS as the right cloud provider for your organization Choose the most appropriate service from AWS for a particular use case or project Implement change and operations management Find out the right resource type and size to balance performance and efficiency Discover how to mitigate risk and enforce security, authentication, and authorization Identify common business scenarios and select the right reference architectures for them Who this book is forThis book is for application and enterprise architects, developers, and operations engineers who want to become well-versed with AWS architectural patterns, best practices, and advanced techniques to build scalable, secure, highly available, and cost-effective solutions in the cloud. Although existing AWS users will find this book most useful, it will also help potential users understand how leveraging AWS can benefit their organization.

Quickly build and deploy machine learning models without managing infrastructure, and improve productivity using Amazon SageMaker's capabilities such as Amazon SageMaker Studio, Autopilot, Experiments, Debugger, and Model Monitor Key Features Build, train, and deploy machine learning models quickly using Amazon SageMaker Analyze, detect, and receive alerts relating to various business problems using machine learning algorithms and techniques Improve productivity by training and fine-tuning machine learning models in production Book DescriptionAmazon SageMaker enables you to quickly build, train, and deploy machine learning (ML) models at scale, without managing any infrastructure. It helps you focus on the ML problem at hand and deploy high-quality models by removing the heavy lifting typically involved in each step of the ML process. This book is a comprehensive guide for data scientists and ML developers who want to learn the ins and outs of Amazon SageMaker. You'll understand how to use various modules of SageMaker as a single toolset to solve the challenges faced in ML. As you progress, you'll cover features such as AutoML, built-in algorithms and frameworks, and the option for writing your own code and algorithms to build ML models. Later, the book will show you how to integrate Amazon SageMaker with popular deep learning libraries such as TensorFlow and PyTorch to increase the capabilities of existing models. You'll also learn to get the models to production faster with minimum effort and at a lower cost. Finally, you'll explore how to use Amazon SageMaker Debugger to analyze, detect, and highlight problems to understand the current model state and improve model accuracy. By the end of this Amazon book, you'll be able to use Amazon SageMaker on the full spectrum of ML workflows, from experimentation, training, and monitoring to scaling, deployment, and automation. What you will learn Create and automate end-to-end machine learning workflows on Amazon Web Services (AWS) Become well-versed with data annotation and preparation techniques Use AutoML features to build and train machine learning models with AutoPilot Create models using built-in algorithms and frameworks and your own code Train computer vision and NLP models using real-world examples Cover training techniques for scaling, model optimization, model debugging, and cost optimization Automate deployment tasks in a variety of configurations using SDK and several automation tools Who this book is forThis book is for software engineers, machine learning developers, data scientists, and AWS users who are new to using Amazon SageMaker and want to build high-quality machine learning models without worrying about infrastructure. Knowledge of AWS basics is required to grasp the concepts covered in this book more effectively. Some understanding of machine learning concepts and the Python programming language will also be beneficial.

Nature-Inspired Computing Paradigms in Systems: Reliability, Availability, Maintainability, Safety and Cost (RAMS+C) and Prognostics and Health Management (PHM) covers several areas that include bioinspired techniques and optimization approaches for system dependability. The book addresses the issue of integration and interaction of the bioinspired techniques in system dependability computing so that intelligent decisions, design, and architectures can be supported. It brings together these emerging areas under the umbrella of bio- and nature-inspired computational intelligence. The primary audience of this book includes experts and developers who want to deepen their understanding of bioinspired computing in basic theory, algorithms, and applications. The book is also intended to be used as a textbook for masters and doctoral students who want to enhance their knowledge and understanding of the role of bioinspired techniques in system dependability.

Master the ins and outs of Google's free-to-use office and productivity software Teach Yourself VISUALLY Google Workspace delivers the ultimate guide to getting the most out of Google's Workspace cloud software. Accomplished author Guy Hart-Davis offers readers the ability to tackle a huge number of everyday productivity problems with Google's intuitive collection of online tools. With over 700 full-color screenshots included to help you learn, you'll discover how to: Manage your online Google Calendar Master the files and folders in your Google Drive storage Customize your folders and navigate your Gmail account Create perfect spreadsheets, presentations, and documents in Google Sheets, Slides, and Docs Perfect for anyone who hopes to make sense of Google's highly practical and free online suite of tools, Teach Yourself VISUALLY Google Workspace also belongs on the bookshelves of those who already find themselves using Workspace and just want to get more out of it.

Design and build high-performance, secure, and scalable Salesforce solutions to meet business demands and gain practical experience using real-world scenarios by creating engaging end-to-end solution presentations Key Features Learn common integration, data migration, and security patterns for designing scalable and reliable solutions on the Salesforce Lightning platform Build an end-to-end delivery framework pipeline for delivering successful projects within specified timelines Gain access to an exclusive book club of skilled Salesforce professionals, to discuss ideas, best practices, and share experiences of designing modern solutions using Salesforce Book DescriptionSalesforce Certified Technical Architect (CTA) is the ultimate certification to validate your knowledge and skills when it comes to designing and building high-performance technical solutions on the Salesforce platform. The CTA certificate is granted after successfully passing the CTA review board exam, which tests your platform expertise and soft skills for communicating your solutions and vision. You'll start with the core concepts that every architect should master, including data lifecycle, integration, and security, and build your aptitude for creating high-level technical solutions. Using real-world examples, you'll explore essential topics such as selecting systems or components for your solutions, designing scalable and secure Salesforce architecture, and planning the development lifecycle and deployments. Finally, you'll work on two full mock scenarios that simulate the review board exam, helping you learn how to identify requirements, create a draft solution, and combine all the elements together to create an engaging story to present in front of the board or to a client in real life. By the end of this Salesforce book, you'll have gained the knowledge and skills required to pass the review board exam and implement architectural best practices and strategies in your day-to-day work. What you will learn Explore data lifecycle management and apply it effectively in the Salesforce ecosystem Design appropriate enterprise integration interfaces to build your connected solution Understand the essential concepts of identity and access management Develop scalable Salesforce data and system architecture Design the project environment and release strategy for your solution Articulate the benefits, limitations, and design considerations relating to your solution Discover tips, tricks, and strategies to prepare for the Salesforce CTA review board exam Who this book is forThis book is for Salesforce architects who want to become certified technical architects by learning how to design secure and scalable technical solutions for their organizations. A solid understanding of the Salesforce platform is required, ideally combined with 3 to 5 years of practical experience as an application architect, system architect, enterprise architect, or solution architect.

Explore a wide range of low-code tools in the Salesforce platform for building customized CRM applications without writing any code Key Features Create apps with a rich user experience without paying for costly developers Leverage Salesforce Lightning Platform's declarative features to build professional-grade applications Improve productivity with business process automation using Workflow, Process Builder, and Flow Book DescriptionLow-code platforms allow users to focus on business logic to create solutions without getting trapped in programming complexities. Thanks to its powerful features for designing, developing, and deploying apps without having to hand-code, Salesforce is at the forefront of the low-code development revolution. This book will guide you in building creative applications for solving your business problems using the declarative framework provided by Salesforce. You'll start by learning how to design your business data model with custom objects, fields, formulas, and validation rules, all secured by the Salesforce security model. You'll then explore tools such as Workflow, Process Builder, Lightning Flow, and Actions that will help you to automate your business processes with ease. This book also shows you how to use Lightning App Builder to build personalized UIs for your Salesforce applications, explains the value of creating community pages for your organization, and teaches you how to customize them with Experience Builder. Finally, you'll work with the sandbox model, deploy your solutions, and deliver an effective release management strategy. By the end of this Salesforce book, you'll be ready to customize Salesforce CRM to meet your business requirements by creating unique solutions without writing a single line of code. What you will learn Get to grips with the fundamentals of data modeling to enhance data quality Deliver dynamic configuration capabilities using custom settings and metadata types Secure your data by implementing the Salesforce security model Customize Salesforce applications with Lightning App Builder Create impressive pages for your community using Experience Builder Use Data Loader to import and export data without writing any code Embrace the Salesforce Ohana culture to share knowledge and learn from the global Salesforce community Who this book is forIf you are a citizen developer, business analyst, Salesforce administrator, or anyone interested in developing applications or solutions for business problems but lack technical knowledge, this book is for you. No prior programming experience is required.

Learn how to extend the capabilities of Power Apps by building code components using Power Apps Component Framework Key Features Understand how to extend Power Apps' capabilities Enhance your skills with the help of practical code components used throughout the book Overcome common challenges, avoid pitfalls, and improve your code Book DescriptionPower Apps Component Framework is used by professional developers to extend the capabilities of model-driven and canvas apps. Extending Microsoft Power Apps with Power Apps Component Framework will take you through the basic as well as advanced topics using practical examples. The book starts by helping you understand the fundamentals of the framework, its lifecycle, and the tools that you'll use to build code components using best practices and file management guidelines. You'll then learn how to extend Power Apps step by step and apply the principles and concepts covered in the book to build code components for field type attributes. The book covers different ways of debugging code components and guides you through the process of building code components for datasets. You'll also explore the functions and methods provided by the framework to enhance your controls using powerful sets of libraries and extensions. As you advance, you'll get to grips with creating and managing authentication profiles, discover different ways of deploying code components, and configure code components in model-driven and canvas apps. Finally, you'll learn some of the important features of the framework and learn modern web development practices. By the end of this Power Apps book, you'll be able to build, debug, enrich, and deploy code components confidently. What you will learn Understand the fundamentals of Power Apps Component Framework Explore the tools that make it easy to build code components Build code components for both a field and a dataset Debug using test harness and Fiddler Implement caching techniques Find out how to work with the Dataverse Web API Build code components using React and Fluent UI controls Discover different deployment strategies Who this book is forThis book is for developers who are looking to build advanced skills for extending the capabilities of Power Apps. Basic knowledge of Power Apps and web development is necessary to get started with this book.

Secure your container environment against cyberattacks and deliver robust deployments with this practical guide Key Features Explore a variety of Kubernetes components that help you to prevent cyberattacks Perform effective resource management and monitoring with Prometheus and built-in Kubernetes tools Learn techniques to prevent attackers from compromising applications and accessing resources for crypto-coin mining Book DescriptionKubernetes is an open source orchestration platform for managing containerized applications. Despite widespread adoption of the technology, DevOps engineers might be unaware of the pitfalls of containerized environments. With this comprehensive book, you'll learn how to use the different security integrations available on the Kubernetes platform to safeguard your deployments in a variety of scenarios. Learn Kubernetes Security starts by taking you through the Kubernetes architecture and the networking model. You'll then learn about the Kubernetes threat model and get to grips with securing clusters. Throughout the book, you'll cover various security aspects such as authentication, authorization, image scanning, and resource monitoring. As you advance, you'll learn about securing cluster components (the kube-apiserver, CoreDNS, and kubelet) and pods (hardening image, security context, and PodSecurityPolicy). With the help of hands-on examples, you'll also learn how to use open source tools such as Anchore, Prometheus, OPA, and Falco to protect your deployments. By the end of this Kubernetes book, you'll have gained a solid understanding of container security and be able to protect your clusters from cyberattacks and mitigate cybersecurity threats. What you will learn Understand the basics of Kubernetes architecture and networking Gain insights into different security integrations provided by the Kubernetes platform Delve into Kubernetes' threat modeling and security domains Explore different security configurations from a variety of practical examples Get to grips with using and deploying open source tools to protect your deployments Discover techniques to mitigate or prevent known Kubernetes hacks Who this book is forThis book is for security consultants, cloud administrators, system administrators, and DevOps engineers interested in securing their container deployments. If you're looking to secure your Kubernetes clusters and cloud-based deployments, you'll find this book useful. A basic understanding of cloud computing and containerization is necessary to make the most of this book.