Hands-on Azure Functions with C#
Build serverless solutions using Azure Functions. This book provides you with a deep understanding of Azure Functions so you can build highly scalable and reliable serverless applications. The book starts with an introduction to Azure Functions and demonstrates triggers and bindings with use cases. The process to build an OTP mailer with Queue Storage Trigger and SendGrid output binding is presented, and timer triggers and blob storage binding are covered. Creating custom binding for Azure Functions and building a serverless API using Azure Functions and Azure SQL are discussed. You will know how to build a serverless API using Azure Functions and Azure Cosmos DB, and you will go over enabling application insights and Azure Monitor. Storing function secrets in Azure Key Vault is discussed as well as authentication and authorization using Azure Active Directory. You will learn how to secure your serverless apps using API Management and deploy your Azure Functions using IDEs. Deplo ...
Build serverless solutions using Azure Functions. This book provides you with a deep understanding of Azure Functions so you can build highly scalable and reliable serverless applications. The book starts with an introduction to Azure Functions and demonstrates triggers and bindings with use cases. The process to build an OTP mailer with Queue Storage Trigger and SendGrid output binding is presented, and timer triggers and blob storage binding are covered. Creating custom binding for Azure Functions and building a serverless API using Azure Functions and Azure SQL are discussed. You will know how to build a serverless API using Azure Functions and Azure Cosmos DB, and you will go over enabling application insights and Azure Monitor. Storing function secrets in Azure Key Vault is discussed as well as authentication and authorization using Azure Active Directory. You will learn how to secure your serverless apps using API Management and deploy your Azure Functions using IDEs. Deplo ...
Spring Boot with React and AWS
Create and deploy full-stack Spring Boot applications with React and AWS. This practical and authoritative guide teaches you the fundamentals of Amazon Web Services with no prior experience. You will start by learning the fundamentals of AWS, including EC2, S3, IAM, and load balancer. Next, you will learn to deploy a Spring Boot REST API to AWS with Elastic Beanstalk, which will give you the ability to build and deploy a Spring Boot application. You will explore the RDS relational database and create an instance of a MySQL database in AWS with RDS. You will then deploy a Spring Boot application to MySQL in AWS and deploy a full-stack Spring Boot React application to AWS using Elastic Beanstalk and S3. Lastly, you will be introduced to ELB, CloudWatch, and Route 53. By the end of this book you will understand full-stack Spring Boot React applications and their deployment. If you prefer "learning by coding" then Spring Boot with React and AWS is the book for you. ...
Create and deploy full-stack Spring Boot applications with React and AWS. This practical and authoritative guide teaches you the fundamentals of Amazon Web Services with no prior experience. You will start by learning the fundamentals of AWS, including EC2, S3, IAM, and load balancer. Next, you will learn to deploy a Spring Boot REST API to AWS with Elastic Beanstalk, which will give you the ability to build and deploy a Spring Boot application. You will explore the RDS relational database and create an instance of a MySQL database in AWS with RDS. You will then deploy a Spring Boot application to MySQL in AWS and deploy a full-stack Spring Boot React application to AWS using Elastic Beanstalk and S3. Lastly, you will be introduced to ELB, CloudWatch, and Route 53. By the end of this book you will understand full-stack Spring Boot React applications and their deployment. If you prefer "learning by coding" then Spring Boot with React and AWS is the book for you. ...
Pro Java Microservices with Quarkus and Kubernetes
Build and design microservices using Java and the Red Hat Quarkus Framework. This book will help you quickly get started with the features and concerns of a microservices architecture. It will introduce Docker and Kubernetes to help you deploy your microservices. You will be guided on how to install the appropriate tools to work properly. For those who are new to enterprise development using Quarkus, you will be introduced to its core principles and main features through a deep step-by-step tutorial. For experts, this book offers some recipes that illustrate how to split monoliths and implement microservices and deploy them as containers to Kubernetes. By the end of reading this book, you will have practical hands-on experience of building microservices using Quarkus and you will master deploying them to Kubernetes. ...
Build and design microservices using Java and the Red Hat Quarkus Framework. This book will help you quickly get started with the features and concerns of a microservices architecture. It will introduce Docker and Kubernetes to help you deploy your microservices. You will be guided on how to install the appropriate tools to work properly. For those who are new to enterprise development using Quarkus, you will be introduced to its core principles and main features through a deep step-by-step tutorial. For experts, this book offers some recipes that illustrate how to split monoliths and implement microservices and deploy them as containers to Kubernetes. By the end of reading this book, you will have practical hands-on experience of building microservices using Quarkus and you will master deploying them to Kubernetes. ...
First Semester in Numerical Analysis with Python
The book is based on "First semester in Numerical Analysis with Julia". The contents of the original book are retained, while all the algorithms are implemented in Python (Version 3.8.0). Python is an open source (under OSI), interpreted, general-purpose programming language that has a large number of users around the world. Python is ranked the third in August 2020 by the TIOBE programming community index 2 , a measure of popularity of programming languages, and is the top-ranked interpreted language. We hope this book will better serve readers who are interested in a first course in Numerical Analysis, but are more familiar with Python for the implementation of the algorithms. The first chapter of the book has a self-contained tutorial for Python, including how to set up the computer environment. Anaconda, the open-source individual edition, is recommended for an easy installation of Python and effortless management of Python packages, and the Jupyter environment, a web-based inte ...
The book is based on "First semester in Numerical Analysis with Julia". The contents of the original book are retained, while all the algorithms are implemented in Python (Version 3.8.0). Python is an open source (under OSI), interpreted, general-purpose programming language that has a large number of users around the world. Python is ranked the third in August 2020 by the TIOBE programming community index 2 , a measure of popularity of programming languages, and is the top-ranked interpreted language. We hope this book will better serve readers who are interested in a first course in Numerical Analysis, but are more familiar with Python for the implementation of the algorithms. The first chapter of the book has a self-contained tutorial for Python, including how to set up the computer environment. Anaconda, the open-source individual edition, is recommended for an easy installation of Python and effortless management of Python packages, and the Jupyter environment, a web-based inte ...
Pipeline as Code
Pipeline as Code is a practical guide to automating your development pipeline in a cloud-native, service-driven world. You'll use the latest infrastructure-as-code tools like Packer and Terraform to develop reliable CI/CD pipelines for numerous cloud-native applications. Follow this book's insightful best practices, and you'll soon be delivering software that's quicker to market, faster to deploy, and with less last-minute production bugs. Treat your CI/CD pipeline like the real application it is. With the Pipeline as Code approach, you create a collection of scripts that replace the tedious web UI wrapped around most CI/CD systems. Code-driven pipelines are easy to use, modify, and maintain, and your entire CI pipeline becomes more efficient because you directly interact with core components like Jenkins, Terraform, and Docker. In Pipeline as Code you'll learn to build reliable CI/CD pipelines for cloud-native applications. With Jenkins as the backbone, you'll programmatically c ...
Pipeline as Code is a practical guide to automating your development pipeline in a cloud-native, service-driven world. You'll use the latest infrastructure-as-code tools like Packer and Terraform to develop reliable CI/CD pipelines for numerous cloud-native applications. Follow this book's insightful best practices, and you'll soon be delivering software that's quicker to market, faster to deploy, and with less last-minute production bugs. Treat your CI/CD pipeline like the real application it is. With the Pipeline as Code approach, you create a collection of scripts that replace the tedious web UI wrapped around most CI/CD systems. Code-driven pipelines are easy to use, modify, and maintain, and your entire CI pipeline becomes more efficient because you directly interact with core components like Jenkins, Terraform, and Docker. In Pipeline as Code you'll learn to build reliable CI/CD pipelines for cloud-native applications. With Jenkins as the backbone, you'll programmatically c ...
Deep Learning with Python, 2nd Edition
Deep Learning with Python has taught thousands of readers how to put the full capabilities of deep learning into action. This extensively revised second edition introduces deep learning using Python and Keras, and is loaded with insights for both novice and experienced ML practitioners. You'll learn practical techniques that are easy to apply in the real world, and important theory for perfecting neural networks. Recent innovations in deep learning unlock exciting new software capabilities like automated language translation, image recognition, and more. Deep learning is quickly becoming essential knowledge for every software developer, and modern tools like Keras and TensorFlow put it within your reach - even if you have no background in mathematics or data science. This book shows you how to get started. Deep Learning with Python, Second Edition introduces the field of deep learning using Python and the powerful Keras library. In this revised and expanded new edition, Keras cre ...
Deep Learning with Python has taught thousands of readers how to put the full capabilities of deep learning into action. This extensively revised second edition introduces deep learning using Python and Keras, and is loaded with insights for both novice and experienced ML practitioners. You'll learn practical techniques that are easy to apply in the real world, and important theory for perfecting neural networks. Recent innovations in deep learning unlock exciting new software capabilities like automated language translation, image recognition, and more. Deep learning is quickly becoming essential knowledge for every software developer, and modern tools like Keras and TensorFlow put it within your reach - even if you have no background in mathematics or data science. This book shows you how to get started. Deep Learning with Python, Second Edition introduces the field of deep learning using Python and the powerful Keras library. In this revised and expanded new edition, Keras cre ...
First Semester in Numerical Analysis with Python
The book is based on "First semester in Numerical Analysis with Julia". The contents of the original book are retained, while all the algorithms are implemented in Python (Version 3.8.0). Python is an open source (under OSI), interpreted, general-purpose programming language that has a large number of users around the world. Python is ranked the third in August 2020 by the TIOBE programming community index 2 , a measure of popularity of programming languages, and is the top-ranked interpreted language. We hope this book will better serve readers who are interested in a first course in Numerical Analysis, but are more familiar with Python for the implementation of the algorithms. The first chapter of the book has a self-contained tutorial for Python, including how to set up the computer environment. Anaconda, the open-source individual edition, is recommended for an easy installation of Python and effortless management of Python packages, and the Jupyter environment, a web-based inte ...
The book is based on "First semester in Numerical Analysis with Julia". The contents of the original book are retained, while all the algorithms are implemented in Python (Version 3.8.0). Python is an open source (under OSI), interpreted, general-purpose programming language that has a large number of users around the world. Python is ranked the third in August 2020 by the TIOBE programming community index 2 , a measure of popularity of programming languages, and is the top-ranked interpreted language. We hope this book will better serve readers who are interested in a first course in Numerical Analysis, but are more familiar with Python for the implementation of the algorithms. The first chapter of the book has a self-contained tutorial for Python, including how to set up the computer environment. Anaconda, the open-source individual edition, is recommended for an easy installation of Python and effortless management of Python packages, and the Jupyter environment, a web-based inte ...
Architect Modern Web Applications with ASP.NET Core and Azure
The audience for this guide is mainly developers, development leads, and architects who are interested in building modern web applications using Microsoft technologies and services in the cloud. A secondary audience is technical decision makers who are already familiar ASP.NET or Azure and are looking for information on whether it makes sense to upgrade to ASP.NET Core for new or existing projects. This guide has been condensed into a relatively small document that focuses on building web applications with modern .NET technologies and Azure. As such, it can be read in its entirety to provide a foundation of understanding such applications and their technical considerations. The guide, along with its sample application, can also serve as a starting point or reference. Use the associated sample application as a template for your own applications, or to see how you might organize your application's component parts. Refer back to the guide's principles and coverage of architecture an ...
The audience for this guide is mainly developers, development leads, and architects who are interested in building modern web applications using Microsoft technologies and services in the cloud. A secondary audience is technical decision makers who are already familiar ASP.NET or Azure and are looking for information on whether it makes sense to upgrade to ASP.NET Core for new or existing projects. This guide has been condensed into a relatively small document that focuses on building web applications with modern .NET technologies and Azure. As such, it can be read in its entirety to provide a foundation of understanding such applications and their technical considerations. The guide, along with its sample application, can also serve as a starting point or reference. Use the associated sample application as a template for your own applications, or to see how you might organize your application's component parts. Refer back to the guide's principles and coverage of architecture an ...
Practical Python Data Wrangling and Data Quality
The world around us is full of data that holds unique insights and valuable stories, and this book will help you uncover them. Whether you already work with data or want to learn more about its possibilities, the examples and techniques in this practical book will help you more easily clean, evaluate, and analyze data so that you can generate meaningful insights and compelling visualizations. Complementing foundational concepts with expert advice, author Susan E. McGregor provides the resources you need to extract, evaluate, and analyze a wide variety of data sources and formats, along with the tools to communicate your findings effectively. This book delivers a methodical, jargon-free way for data practitioners at any level, from true novices to seasoned professionals, to harness the power of data. Use Python 3.8+ to read, write, and transform data from a variety of sources; Understand and use programming basics in Python to wrangle data at scale; Organize, document, and structu ...
The world around us is full of data that holds unique insights and valuable stories, and this book will help you uncover them. Whether you already work with data or want to learn more about its possibilities, the examples and techniques in this practical book will help you more easily clean, evaluate, and analyze data so that you can generate meaningful insights and compelling visualizations. Complementing foundational concepts with expert advice, author Susan E. McGregor provides the resources you need to extract, evaluate, and analyze a wide variety of data sources and formats, along with the tools to communicate your findings effectively. This book delivers a methodical, jargon-free way for data practitioners at any level, from true novices to seasoned professionals, to harness the power of data. Use Python 3.8+ to read, write, and transform data from a variety of sources; Understand and use programming basics in Python to wrangle data at scale; Organize, document, and structu ...
Machine Learning for Financial Risk Management with Python
Financial risk management is quickly evolving with the help of artificial intelligence. With this practical book, developers, programmers, engineers, financial analysts, risk analysts, and quantitative and algorithmic analysts will examine Python-based machine learning and deep learning models for assessing financial risk. Building hands-on AI-based financial modeling skills, you'll learn how to replace traditional financial risk models with ML models. Author Abdullah Karasan helps you explore the theory behind financial risk modeling before diving into practical ways of employing ML models in modeling financial risk using Python. With this book, you will: Review classical time series applications and compare them with deep learning models; Explore volatility modeling to measure degrees of risk, using support vector regression, neural networks, and deep learning; Improve market risk models (VaR and ES) using ML techniques and including liquidity dimension; Develop a credit risk anal ...
Financial risk management is quickly evolving with the help of artificial intelligence. With this practical book, developers, programmers, engineers, financial analysts, risk analysts, and quantitative and algorithmic analysts will examine Python-based machine learning and deep learning models for assessing financial risk. Building hands-on AI-based financial modeling skills, you'll learn how to replace traditional financial risk models with ML models. Author Abdullah Karasan helps you explore the theory behind financial risk modeling before diving into practical ways of employing ML models in modeling financial risk using Python. With this book, you will: Review classical time series applications and compare them with deep learning models; Explore volatility modeling to measure degrees of risk, using support vector regression, neural networks, and deep learning; Improve market risk models (VaR and ES) using ML techniques and including liquidity dimension; Develop a credit risk anal ...