Verleger: Packt Publishing
Founded in 2004 in Birmingham, UK, Packt's mission is to help the world put software to work in new ways, through the delivery of effective learning and information services to IT professionals. Working towards that vision, we have published over 6,500 books and videos so far, providing IT professionals with the actionable knowledge they need to get the job done - whether that's specific learning on an emerging technology or optimizing key skills in more established tools. As part of our mission, we have also awarded over $1,000,000 through our Open Source Project Royalty scheme, helping numerous projects become household names along the way.
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Learning Bing Maps API. Bing Maps are a great resource and very versatile when you know how. And this book will show you how, covering everything from embedding on a web page to customizing with your own styles and geo-data

Artan Sinani

Provided as a part of Microsoft's Bing suite of search engines, Bing Maps is a web mapping service powered by the Bing Maps for Enterprise framework. The need for geospatial data has increased dramatically in the last few years. Adding a mapping context to any location-based data is becoming more and more common, and businesses are embracing it to improve their user experience with new data richness. Comprising of simple, follow-along examples, Learning Bing Maps API will show you how to use the many features of Bing Maps, from dropping a simple map on a web page, to fetching geospatial data from the Microsoft servers. Through the course of this book you will build a solid foundation for creating your own geo-applications.Following the hands-on recipes of this book, you will build a different web app in each chapter as you communicate with different APIs provided by Bing Maps. You will build your own library of JavaScript modules that talk to the Microsoft Maps API.You will create a custom theme for the map, with your own controls. Taking advantage of the global reach of Bing Maps, you will learn how to build a route scheduler for a delivery company in Madrid, Spain, and then you will discover how to create jobs on the Bing Maps servers for geocoding addresses in California, USA. By the end of the book you will have learned everything you need to know to embed a map on a web page, with your own geo-data, or data obtained by the Bing Map Services.

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Hands-On RESTful Web Services with Go. Develop elegant RESTful APIs with Golang for microservices and the cloud - Second Edition

Naren Yellavula

Building RESTful web services can be tough as there are countless standards and ways to develop API. In modern architectures such as microservices, RESTful APIs are common in communication, making idiomatic and scalable API development crucial. This book covers basic through to advanced API development concepts and supporting tools.You’ll start with an introduction to REST API development before moving on to building the essential blocks for working with Go. You’ll explore routers, middleware, and available open source web development solutions in Go to create robust APIs, and understand the application and database layers to build RESTful web services. You’ll learn various data formats like protocol buffers and JSON, and understand how to serve them over HTTP and gRPC. After covering advanced topics such as asynchronous API design and GraphQL for building scalable web services, you’ll discover how microservices can benefit from REST. You’ll also explore packaging artifacts in the form of containers and understand how to set up an ideal deployment ecosystem for web services. Finally, you’ll cover the provisioning of infrastructure using infrastructure as code (IaC) and secure your REST API.By the end of the book, you’ll have intermediate knowledge of web service development and be able to apply the skills you’ve learned in a practical way.

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Mastering Azure Machine Learning. Perform large-scale end-to-end advanced machine learning in the cloud with Microsoft Azure Machine Learning

Christoph Körner, Kaijisse Waaijer

The increase being seen in data volume today requires distributed systems, powerful algorithms, and scalable cloud infrastructure to compute insights and train and deploy machine learning (ML) models. This book will help you improve your knowledge of building ML models using Azure and end-to-end ML pipelines on the cloud.The book starts with an overview of an end-to-end ML project and a guide on how to choose the right Azure service for different ML tasks. It then focuses on Azure Machine Learning and takes you through the process of data experimentation, data preparation, and feature engineering using Azure Machine Learning and Python. You'll learn advanced feature extraction techniques using natural language processing (NLP), classical ML techniques, and the secrets of both a great recommendation engine and a performant computer vision model using deep learning methods. You'll also explore how to train, optimize, and tune models using Azure Automated Machine Learning and HyperDrive, and perform distributed training on Azure. Then, you'll learn different deployment and monitoring techniques using Azure Kubernetes Services with Azure Machine Learning, along with the basics of MLOps—DevOps for ML to automate your ML process as CI/CD pipeline.By the end of this book, you'll have mastered Azure Machine Learning and be able to confidently design, build and operate scalable ML pipelines in Azure.