Hands-On Artificial Intelligence on Google Cloud Platform: Build intelligent applications powered by: TensorFlow,Cloud AutoML,BigQuery,and Dialogflow
by: Anand Deshpande
Print Length 页数: 350 pages
Publisher finelybook 出版社: Packt Publishing (March 6,2020)
Language 语言: English
ISBN-10: 1789538467
ISBN-13: 9781789538465
Book Description
By finelybook
Develop robust AI applications with TensorFlow,Cloud AutoML,TPUs,and other GCP services
With a wide range of exciting tools and libraries such as Google BigQuery,Google Cloud Dataflow,and Google Cloud Dataproc,Google Cloud Platform (GCP) enables efficient big data processing and the development of smart AI models on the cloud. This GCP book will guide you in using these tools to build your AI-powered applications with ease and managing thousands of AI implementations on the cloud to help save you time.
Starting with a brief overview of Cloud AI and GCP features,you’ll learn how to deal with large volumes of data using auto-scaling features. You’ll then implement Cloud AutoML to demonstrate the use of streaming components for performing data analytics and understand how Dialogflow can be used to create a conversational interface. As you advance,you’ll be able to scale out and speed up AI and predictive applications using TensorFlow. You’ll also leverage GCP to train and optimize deep learning models,run machine learning algorithms,and perform complex GPU computations using TPUs. Finally,you’ll build and deploy AI applications to production with the help of an end-to-end use case.
By the end of this book,you’ll have learned how to design and run experiments and be able to discover innovative solutions without worrying about infrastructure,resources,and computing power.
What you will learn
Understand the basics of cloud computing and explore GCP components
Work with the data ingestion and preprocessing techniques in GCP for machine learning
Implement machine learning algorithms with Google Cloud AutoML
Optimize TensorFlow machine learning with Google Cloud TPUs
Get to grips with operationalizing AI on GCP
Build an end-to-end machine learning pipeline using Cloud Storage,Cloud Dataflow,and Cloud Datalab
Build models from petabytes of structured and semi-structured data using BigQuery ML
Contents
Preface
Section 1: Basics of Google Cloud Platform
Chapter 1: Overview of Al and GCP
Chapter 2: Computing and Processing Using GCP Components
Section 2: Artificial Intelligence with Google Cloud Platform
Chapter 3: Machine Learning Applications with XGBoost
Chapter 4: Using Cloud AutoML
Chapter 5: Building a Big Data Cloud Machine Learning Engine
Chapter 6: Smart Conversational Applications Using DialogFlow
Section 3: TensorFlow on Google Cloud Platform
Chapter 7: Understanding Cloud TPUs
Chapter 8: Implementing TensorFlow Models Using Cloud ML Engine
Chapter 9: Building Prediction Applications
Section 4: Building Applications and Upcoming Features
Chapter 10: Building an Al application
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