Automated Machine Learning on AWS. Fast-track the development of your production-ready machine learning applications the AWS way

Trenton Potgieter, Jonathan Dahlberg

AWS provides a wide range of solutions to help automate a machine learning workflow with just a few lines of code. With this practical book, you'll learn how to automate a machine learning pipeline using the various AWS services.Automated Machine Learning on AWS begins with a quick overview of what the machine learning pipeline/process looks like and highlights the typical challenges that you may face when building a pipeline. Throughout the book, you'll become well versed with various AWS solutions such as Amazon SageMaker Autopilot, AutoGluon, and AWS Step Functions to automate an end-to-end ML process with the help of hands-on examples. The book will show you how to build, monitor, and execute a CI/CD pipeline for the ML process and how the various CI/CD services within AWS can be applied to a use case with the Cloud Development Kit (CDK). You'll understand what a data-centric ML process is by working with the Amazon Managed Services for Apache Airflow and then build a managed Airflow environment. You'll also cover the key success criteria for an MLSDLC implementation and the process of creating a self-mutating CI/CD pipeline using AWS CDK from the perspective of the platform engineering team.By the end of this AWS book, you'll be able to effectively automate a complete machine learning pipeline and deploy it to production.

Automated Machine Learning with AutoKeras. Deep learning made accessible for everyone with just few lines of coding

Luis Sobrecueva

AutoKeras is an AutoML open-source software library that provides easy access to deep learning models. If you are looking to build deep learning model architectures and perform parameter tuning automatically using AutoKeras, then this book is for you.This book teaches you how to develop and use state-of-the-art AI algorithms in your projects. It begins with a high-level introduction to automated machine learning, explaining all the concepts required to get started with this machine learning approach. You will then learn how to use AutoKeras for image and text classification and regression. As you make progress, you'll discover how to use AutoKeras to perform sentiment analysis on documents. This book will also show you how to implement a custom model for topic classification with AutoKeras. Toward the end, you will explore advanced concepts of AutoKeras such as working with multi-modal data and multi-task, customizing the model with AutoModel, and visualizing experiment results using AutoKeras Extensions.By the end of this machine learning book, you will be able to confidently use AutoKeras to design your own custom machine learning models in your company.

Automated Machine Learning with Microsoft Azure. Build highly accurate and scalable end-to-end AI solutions with Azure AutoML

Dennis Michael Sawyers

Automated Machine Learning with Microsoft Azure will teach you how to build high-performing, accurate machine learning models in record time. It will equip you with the knowledge and skills to easily harness the power of artificial intelligence and increase the productivity and profitability of your business. Guided user interfaces (GUIs) enable both novices and seasoned data scientists to easily train and deploy machine learning solutions to production. Using a careful, step-by-step approach, this book will teach you how to use Azure AutoML with a GUI as well as the AzureML Python software development kit (SDK).First, you'll learn how to prepare data, train models, and register them to your Azure Machine Learning workspace. You'll then discover how to take those models and use them to create both automated batch solutions using machine learning pipelines and real-time scoring solutions using Azure Kubernetes Service (AKS). Finally, you will be able to use AutoML on your own data to not only train regression, classification, and forecasting models but also use them to solve a wide variety of business problems.By the end of this Azure book, you'll be able to show your business partners exactly how your ML models are making predictions through automatically generated charts and graphs, earning their trust and respect.

Automated Testing in Microsoft Dynamics 365 Business Central. Efficiently automate test cases for faster development cycles with less time needed for manual testing - Second Edition

Luc van Vugt

Dynamics 365 Business Central is a cloud-based SaaS ERP proposition from Microsoft. With development practices becoming more formal, implementing changes or new features is not as simple as it used to be back when Dynamics 365 Business Central was called Navigator, Navision Financials, or Microsoft Business Solutions-Navision, and the call for test automation is increasing.This book will show you how to leverage the testing tools available in Dynamics 365 Business Central to perform automated testing. Starting with a quick introduction to automated testing and test-driven development (TDD), you'll get an overview of test automation in Dynamics 365 Business Central. You'll then learn how to design and build automated tests and explore methods to progress from requirements to application and testing code. Next, you'll find out how you can incorporate your own as well as Microsoft tests into your development practice. With the addition of three new chapters, this second edition covers in detail how to construct complex scenarios, write testable code, and test processes with incoming and outgoing calls.By the end of this book, you'll be able to write your own automated tests for Microsoft Business Central.

Automated Testing in Microsoft Dynamics 365 Business Central. Efficiently automate test cases in Dynamics NAV and Business Central

Luc van Vugt

Dynamics 365 Business Central is the new cloud-based SaaS ERP proposition from Microsoft. It’s not as simple as it used to be way back when it was called Navigator, Navision Financials, or Microsoft Business Solutions-Navision. Our development practices are becoming more formal, and with this, the call for test automation is pressing on us.This book will teach you to leverage testing tools available with Dynamics 365 Business Central to perform automated testing. We’ll begin with a quick introduction to automated testing, followed by an overview of test automation in Dynamics 365 Business Central. Then you’ll learn to design and build automated tests and we’ll go through some efficient methods to get from requirements to application and testing code. Lastly, you’ll learn to incorporate your own and Microsoft tests into your daily development practice.By the end of the book, you’ll be able to write your own automated tests for Dynamics 365 Business Central.

Automating DevOps with GitLab CI/CD Pipelines. Build efficient CI/CD pipelines to verify, secure, and deploy your code using real-life examples

Christopher Cowell, Nicholas Lotz, Chris Timberlake

Developers and release engineers understand the high stakes of building, packaging, and deploying code efficiently. Ensuring that your code is fast, secure, and functionally correct can be a time-consuming and complex task. GitLab CI/CD pipelines simplify these tasks, enabling automation and seamless deployment.Automating DevOps with GitLab CI/CD Pipelines starts with the fundamentals of Git and GitLab, guiding you through committing and reviewing code. You'll learn how to set up GitLab Runners to execute and autoscale CI/CD pipelines, configure pipelines for different stages of the software development lifecycle, and analyze pipeline results in GitLab. As you progress, you'll gain expertise in deploying code across environments, integrating GitLab with Kubernetes and Terraform, triggering pipelines, and improving pipeline performance. This book also includes troubleshooting techniques, best practices, real-world use cases, and self-assessments to reinforce key CI/CD concepts and help you prepare for GitLab-related interviews and certifications.By the end of this book, you'll have the skills to build and automate CI/CD pipelines in GitLab, streamline DevOps workflows, and deploy high-quality, secure code with confidence.

Automating Salesforce Marketing Cloud. Reap all the benefits of the SFMC platform and increase your productivity with the help of real-world examples

Greg Gifford, Jason Hanshaw, Guilda Hilaire

Salesforce Marketing Cloud (SFMC) allows you to use multiple channels and tools to create a 1:1 marketing experience for your customers and subscribers. Through automation and helper tasks, you can greatly increase your productivity while also reducing the level of effort required in terms of volume and frequency.Automating Salesforce Marketing Cloud starts by discussing what automation is generally and then progresses to what automation is in SFMC. After that, you’ll focus on how to perform automation inside of SFMC all the way to fully running processes and capabilities from an external service. Later chapters explore the benefits and capabilities of automation and having an automation mindset both within and outside of SFMC. Equipped with this knowledge and example code, you'll be prepared to maximize your SFMC efficiency.By the end of this Salesforce book, you’ll have the skills you need to build automation both inside and outside of SFMC, along with the knowledge for using the platform optimally.

Automating Security Detection Engineering. A hands-on guide to implementing Detection as Code

Dennis Chow, David Bruskin

Today's global enterprise security programs grapple with constantly evolving threats. Even though the industry has released abundant security tools, most of which are equipped with APIs for integrations, they lack a rapid detection development work stream. This book arms you with the skills you need to automate the development, testing, and monitoring of detection-based use cases.You’ll start with the technical architecture, exploring where automation is conducive throughout the detection use case lifecycle. With the help of hands-on labs, you’ll learn how to utilize threat-informed defense artifacts and then progress to creating advanced AI-powered CI/CD pipelines to bolster your Detection as Code practices. Along the way, you'll develop custom code for EDRs, WAFs, SIEMs, CSPMs, RASPs, and NIDS. The book will also guide you in developing KPIs for program monitoring and cover collaboration mechanisms to operate the team with DevSecOps principles. Finally, you'll be able to customize a Detection as Code program that fits your organization's needs.By the end of the book, you'll have gained the expertise to automate nearly the entire use case development lifecycle for any enterprise.