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 testin ...
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 learning, and ...
Pro Google Kubernetes Engine
Discover methodologies and best practices for getting started with Google Kubernetes Engine (GKE). This book helps you understand how GKE provides a fully managed environment to deploy and operate containerized applications on Google Cloud infrastructure.
You will see how Kubernetes makes it easier for users to manage clusters and the container ecosystem. And you will get detailed guidance on deploying and managing applications, handling administration of container clusters, managing policies, and monitoring cluster resources. You will learn how to operate the GKE environment through the GUI-based Google Cloud console and the "gcloud" command line interface.
The book starts with an introduction to GKE and associated services. The authors provide hands-on examples to set up Container Registry and GKE Cluster, and you will follow through an application deployment on GKE. Later chapters focus on securing your GCP GKE environment, GKE monitoring and dashboarding, ...
Cognitive Virtual Assistants Using Google Dialogflow
Follow a step-by-step, hands-on approach to building production-ready enterprise cognitive virtual assistants using Google Dialogflow. This book provides an overview of the various cognitive technology choices available and takes a deep dive into cognitive virtual agents for handling complex real-life use cases in various industries such as travel and weather.
You'll delve deeper into the advanced features of cognitive virtual assistants implementing features such as input/output context, follow-up intents, actions and parameters, and handling complex multiple intents. You'll learn how to integrate with third-party messaging platforms by integrating your cognitive bot with Facebook messenger. You'll also integrate with third-party APIs to enrich your cognitive bots using webhooks.
Cognitive Virtual Assistants Using Google Dialogflow takes the complexity out of the cognitive platform and provides rich guidance which you can use when developing your own cognitive bots ...
Software Engineering at Google
Today, software engineers need to know not only how to program effectively but also how to develop proper engineering practices to make their codebase sustainable and healthy. This book emphasizes this difference between programming and software engineering.
How can software engineers manage a living codebase that evolves and responds to changing requirements and demands over the length of its life? Based on their experience at Google software engineers Titus Winters and Hyrum Wright, along with technical writer Tom Manshreck, present a candid and insightful look at how some of the world's leading practitioners construct and maintain software. This book covers Google's unique engineering culture, processes, and tools and how these aspects contribute to the effectiveness of an engineering organization.
You'll explore three fundamental principles that software organizations should keep in mind when designing, architecting, writing, and maintaining code: How time affects the ...
Hands On Google Cloud SQL and Cloud Spanner
Discover the methodologies and best practices for getting started with Google Cloud Platform relational services - CloudSQL and CloudSpanner.
The book begins with the basics of working with the Google Cloud Platform along with an introduction to the database technologies available for developers from Google Cloud. You'll then take an in-depth hands on journey into Google CloudSQL and CloudSpanner, including choosing the right platform for your application needs, planning, provisioning, designing and developing your application.
Sample applications are given that use Python to connect to CloudSQL and CloudSpanner, along with helpful features provided by the engines. You''ll also implement practical best practices in the last chapter. Hands On Google Cloud SQL and Cloud Spanner is a great starting point to apply GCP data offerings in your technology stack and the code used allows you to try out the examples and extend them in interesting ways.
Beginning Kubernetes on the Google Cloud Platform
Use this beginner's guide to understand and work with Kubernetes on the Google Cloud Platform and go from single monolithic Pods (the smallest unit deployed and managed by Kubernetes) all the way up to distributed, fault-tolerant stateful backing stores.
You need only a familiarity with Linux, Bash, and Python to successfully use this book. Proficiency in Docker or cloud technology is not required. You will follow a learn-by-doing approach, running small experiments and observing the effects.
Google open sourced Kubernetes in 2015 and now it is the industry standard in container orchestration. It has been adopted by all leading vendors of cloud, on-prem, and hybrid infrastructure services: Microsoft (Azure AKS), Amazon (AWS EKS), IBM (IBM Cloud Kubernetes Services), Alibaba Cloud (ACK), RedHat (OpenShift), and Pivotal (PKS). Even though Kubernetes is offered by all of the market-leading cloud providers, the Google Cloud Platform (GCP) offers an integrated shell ...
Voice Applications for Alexa and Google Assistant
Voice Applications for Alexa and Google Assistant is your guide to designing, building, and implementing voice-based applications for Alexa and Google Assistant. Inside, you'll learn how to build your own "skills" - the voice app term for actions the device can perform - from scratch.
In 2018, an estimated 100 million voice-controlled devices were installed in homes worldwide, and the apps that control them, like Amazon Alexa and Google Assistant, are getting more powerful, with new skills being added every day. Great voice apps improve how users interact with the web, whether they're checking the weather, asking for sports scores, or playing a game.
About the book
Voice Applications for Alexa and Google Assistant is your guide to designing, building, and implementing voice-based applications for Alexa and Google Assistant. You'll learn to build applications that listen to users, store information, and rely on user context, as you create a voic ...
Google Daydream VR Cookbook
Google's new ARCore and Daydream VR platforms enable you to deliver advanced augmented and virtual reality games and apps on a wide spectrum of modern Android devices. Now for the first time, there's a comprehensive deep dive into both ARCore and Daydream for every Android developer and designer. Multi-award-winning AR/VR developer Sam Keene takes a hands-on approach, leading you through all aspects of the ARCore and Daydream frameworks and SDKs, with step-by-step tutorials and advice for building pro-quality AR/VR games and apps.
Keene presents his material as a cookbook of recipes to get you up and running with VR/AR development as fast and as painlessly as possible. The recipes in most chapters start by assembling the essential building blocks, which are pieced together to create something larger. You are then free to take these building blocks and turn them into your own creation.
Keene also provides an extensive library of downloadable, up-to-the-minute ARCore and Daydream c ...
Google Cloud Platform in Action
Google Cloud Platform in Action teaches you to build and launch applications that scale, leveraging the many services on GCP to move faster than ever. You'll learn how to choose exactly the services that best suit your needs, and you'll be able to build applications that run on Google Cloud Platform and start more quickly, suffer fewer disasters, and require less maintenance.
Thousands of developers worldwide trust Google Cloud Platform, and for good reason. With GCP, you can host your applications on the same infrastructure that powers Search, Maps, and the other Google tools you use daily. You get rock-solid reliability, an incredible array of prebuilt services, and a cost-effective, pay-only-for-what-you-use model. This book gets you started.
Google Cloud Platform in Action teaches you how to deploy scalable cloud applications on GCP. Author and Google software engineer JJ Geewax is your guide as you try everything from hosting a simpl ...
Practical Java Machine Learning
Build machine learning (ML) solutions for Java development. This book shows you that when designing ML apps, data is the key driver and must be considered throughout all phases of the project life cycle. Practical Java Machine Learning helps you understand the importance of data and how to organize it for use within your ML project. You will be introduced to tools which can help you identify and manage your data including JSON, visualization, NoSQL databases, and cloud platforms including Google Cloud Platform and Amazon Web Services.
Practical Java Machine Learning includes multiple projects, with particular focus on the Android mobile platform and features such as sensors, camera, and connectivity, each of which produce data that can power unique machine learning solutions. You will learn to build a variety of applications that demonstrate the capabilities of the Google Cloud Platform machine learning API, including data visualization for Java; document classificatio ...