TensorFlow 2.x in the Colaboratory Cloud
Use TensorFlow 2.x with Google's Colaboratory (Colab) product that offers a free cloud service for Python programmers. Colab is especially well suited as a platform for TensorFlow 2.x deep learning applications. You will learn Colab's default install of the most current TensorFlow 2.x along with Colab's easy access to on-demand GPU hardware acceleration in the cloud for fast execution of deep learning models. This book offers you the opportunity to grasp deep learning in an applied manner with the only requirement being an Internet connection. Everything else - Python, TensorFlow 2.x, GPU support, and Jupyter Notebooks - is provided and ready to go from Colab.
The book begins with an introduction to TensorFlow 2.x and the Google Colab cloud service. You will learn how to provision a workspace on Google Colab and build a simple neural network application. From there you will progress into TensorFlow datasets and building input pipelines in support of modeling and ...
Spring Boot: Up and Running
With over 75 million downloads per month, Spring Boot is the most widely used Java framework available. Its ease and power have revolutionized application development from monoliths to microservices. Yet Spring Boot's simplicity can also be confounding. How do developers learn enough to be productive immediately? This practical book shows you how to use this framework to write successful mission-critical applications.
Mark Heckler from VMware, the company behind Spring, guides you through Spring Boot's architecture and approach, covering topics such as debugging, testing, and deployment. If you want to develop cloud native Java or Kotlin applications with Spring Boot rapidly and effectively (using reactive programming, building APIs, and creating database access of all kinds) this book is for you.
Learn how Spring Boot simplifies cloud native application development and deployment; Build reactive applications and extend communication across the network boundary to c ...
Practical Rust Web Projects
Go beyond the basics of Rust and build web and serverless cloud applications. The applications explained in this practical book include web sites, RESTful APIs, a real-time web chat application, and frontend application with WebAssembly. Each chapter is organized in the following format: what this kind of application looks like; requirements for the example program; an introduction to the Rust libraries used; step-by-step implementation of the example program, including common pitfalls and best practices; and a brief comparison of libraries and frameworks in the same domain.
This book will open your eyes to the world of practical web applications of Rust. After reading the book, you will be able to apply your Rust knowledge to build your own web projects. ...
Kubeflow Operations Guide
Building models is a small part of the story when it comes to deploying machine learning applications. The entire process involves developing, orchestrating, deploying, and running scalable and portable machine learning workloads-a process Kubeflow makes much easier. This practical book shows data scientists, data engineers, and platform architects how to plan and execute a Kubeflow project to make their Kubernetes workflows portable and scalable.
Authors Josh Patterson, Michael Katzenellenbogen, and Austin Harris demonstrate how this open source platform orchestrates workflows by managing machine learning pipelines. You'll learn how to plan and execute a Kubeflow platform that can support workflows from on-premises to cloud providers including Google, Amazon, and Microsoft.
Dive into Kubeflow architecture and learn best practices for using the platform; Understand the process of planning your Kubeflow deployment; Install Kubeflow on an existing on-premise Kubernetes clust ...
Practical AI on the Google Cloud Platform
Working with AI is complicated and expensive for many developers. That's why cloud providers have stepped in to make it easier, offering free (or affordable) state-of-the-art models and training tools to get you started. With this book, you'll learn how to use Google's AI-powered cloud services to do everything from creating a chatbot to analyzing text, images, and video.
Author Micheal Lanham demonstrates methods for building and training models step-by-step and shows you how to expand your models to accomplish increasingly complex tasks. If you have a good grasp of math and the Python language, you'll quickly get up to speed with Google Cloud Platform, whether you want to build an AI assistant or a simple business AI application.
Learn key concepts for data science, machine learning, and deep learning; Explore tools like Video AI and AutoML Tables; Build a simple language processor using deep learning systems; Perform image recognition using CNNs, transfer ...
Learn Microservices with Spring Boot, 2nd Edition
Build Java-based microservices architecture using the Spring Boot framework by evolving an application from a small monolith to an event-driven architecture composed of several services. This revised book follows an incremental approach in teaching the structure of microservices, test-driven development, and common patterns in distributed systems such as service discovery, load balancing, routing, centralized logs, per-environment configuration, and containerization.
This updated book now covers what's been added to the latest Spring Boot release, including support for the latest Java SE; more deep-dive knowledge on how Spring Boot works; testing with JUnit 5; changes in the Spring Cloud tools used for service discovery and load balancing; building Docker images using cloud-native buildpacks; a basic centralized logging solution; E2E traceability with Sleuth; centralized configuration with Consul; many dependency upgrades; support for Spring Data Neumann; and more.
Author Mo ...
Get the authoritative guide to Dapr, the distributed application runtime that works with new and existing programming languages alike. Written by the model's creators, this introduction shows you how Dapr not only unifies stateless, stateful, and actor programming models but also runs everywhere - in the cloud or on the edge.
Authors Haishi Bai and Yaron Schneider, both with Microsoft's Azure CTO team, explain that, with Dapr, you don't need to include any SDKs or libraries in your user code. Instead, you automatically get flexible binding, state management, the actor pattern, pub-sub, reliable messaging, and many more features. This book shows developers, architects, CIOs, students, and computing enthusiasts how to get started with Dapr. ...
Angular for Enterprise-Ready Web Applications, 2nd Edition
This 2nd edition of Angular for Enterprise-Ready Web Applications is updated with in-depth coverage of the evergreen Angular platform.
You'll start by mastering Angular programming fundamentals. Using the Kanban method and GitHub tools, you'll build great-looking apps with Angular Material and also leverage reactive programming patterns with RxJS, discover the flux pattern with NgRx, become familiar with automated testing, utilize continuous integration using CircleCI, and deploy your app to the cloud using Vercel Now and GCloud.
You will then learn how to design and develop line-of-business apps using router-first architecture with observable data anchors, demonstrated through oft-used recipes like master/detail views, and data tables with pagination and forms. Next, you'll discover robust authentication and authorization design demonstrated via integration with Firebase, API documentation using Swagger, and API implementation using the MEAN stack.
Finally, you will le ...
IoT and Edge Computing for Architects, 2nd Edition
Industries are embracing IoT technologies to improve operational expenses, product life, and people's well-being. An architectural guide is needed if you want to traverse the spectrum of technologies needed to build a successful IoT system, whether that's a single device or millions of IoT devices.
IoT and Edge Computing for Architects, Second Edition encompasses the entire spectrum of IoT solutions, from IoT sensors to the cloud. It examines modern sensor systems, focusing on their power and functionality. It also looks at communication theory, paying close attention to near-range PAN, including the new Bluetooth® 5.0 specification and mesh networks. Then, the book explores IP-based communication in LAN and WAN, including 802.11ah, 5G LTE cellular, Sigfox, and LoRaWAN. It also explains edge computing, routing and gateways, and their role in fog computing, as well as the messaging protocols of MQTT 5.0 and CoAP.
With the data now in internet form, you'll get an understanding of ...
Pro ASP.NET Core 3, 8th Edition
Now in its 8th edition, Pro ASP.NET Core has been thoroughly updated for ASP.NET Core 3. This comprehensive, full-color guide is the only book you need to learn ASP.NET Core development!
Professional developers get ready to produce leaner applications for the ASP.NET Core platform. This edition puts ASP.NET Core 3 into context, and takes a deep dive into the tools and techniques required to build modern, extensible web applications. New features and capabilities such as MVC 3, Razor Pages, Blazor Server, and Blazor WebAssembly are covered, along with demonstrations of how they can be applied in practice.
Following the same popular format and style found in previous editions, author Adam Freeman explains how to get the most out of ASP.NET Core 3. Starting with the nuts-and-bolts topics, he teaches readers about middleware components, built-in services, request model binding, and more. Moving along, he introduces increasingly more complex topics and advanced features, including end ...
Beginning Apache Spark Using Azure Databricks
Analyze vast amounts of data in record time using Apache Spark with Databricks in the Cloud. Learn the fundamentals, and more, of running analytics on large clusters in Azure and AWS, using Apache Spark with Databricks on top. Discover how to squeeze the most value out of your data at a mere fraction of what classical analytics solutions cost, while at the same time getting the results you need, incrementally faster.
This book explains how the confluence of these pivotal technologies gives you enormous power, and cheaply, when it comes to huge datasets. You will begin by learning how cloud infrastructure makes it possible to scale your code to large amounts of processing units, without having to pay for the machinery in advance. From there you will learn how Apache Spark, an open source framework, can enable all those CPUs for data analytics use. Finally, you will see how services such as Databricks provide the power of Apache Spark, without you having to know anything about ...