Hands-On Artificial Intelligence on Google Cloud Platform

Deshpande, Anand, Kumar, Manish, Chaudhari, Vikram

  • 出版商: Packt Publishing
  • 出版日期: 2020-03-06
  • 售價: $1,520
  • 貴賓價: 9.5$1,444
  • 語言: 英文
  • 頁數: 350
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1789538467
  • ISBN-13: 9781789538465
  • 相關分類: Google Cloud人工智慧
  • 立即出貨 (庫存=1)

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商品描述

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.

商品描述(中文翻譯)

憑藉著一系列令人興奮的工具和庫,如Google BigQuery、Google Cloud Dataflow和Google Cloud Dataproc,Google Cloud Platform(GCP)能夠在雲端上進行高效的大數據處理和智能AI模型的開發。這本GCP書籍將指導您如何使用這些工具輕鬆構建AI應用程序,並在雲端上管理數千個AI實現,以節省您的時間。

從對雲端AI和GCP功能的簡要概述開始,您將學習如何使用自動擴展功能處理大量數據。然後,您將實施Cloud AutoML,以展示使用流式組件進行數據分析的方法,並了解如何使用Dialogflow創建對話界面。隨著進一步的學習,您將能夠使用TensorFlow擴展和加速AI和預測應用程序。您還將利用GCP來訓練和優化深度學習模型,運行機器學習算法,以及使用TPU執行複雜的GPU計算。最後,您將通過一個端到端的用例來構建和部署AI應用程序到生產環境。

通過閱讀本書,您將學習如何設計和運行實驗,並能夠在不擔心基礎設施、資源和計算能力的情況下發現創新解決方案。

作者簡介

Anand Deshpande

Anand Deshpande has over 19 years' experience with IT services and product development. He is currently working as Vice President of Advanced Analytics and Product Development at VSquare Systems Pvt. Ltd. (VSquare). He has developed a special interest in data science and an algorithmic approach to data management and analytics and co-authored a book entitled Artificial Intelligence for Big Data in May 2018.

Manish Kumar

Manish Kumar works as Director of Technology and Architecture at VSquare. He has over 13 years' experience in providing technology solutions to complex business problems. He has worked extensively on web application development, IoT, big data, cloud technologies, and blockchain. Aside from this book, Manish has co-authored three books (Mastering Hadoop 3, Artificial Intelligence for Big Data, and Building Streaming Applications with Apache Kafka).

Vikram Chaudhari

Vikram Chaudhari works as Director of Data and Advanced Analytics at VSquare. He has over 10 years' IT experience. He is a certified AWS and Google Cloud Architect and has completed multiple implementations of data pipelines with Amazon Web Services and Google Cloud Platform. With implementation experience on multiple data pipelines across platforms, Vikram is instrumental in creating reusable components and accelerators that reduce costs and implementation time.

作者簡介(中文翻譯)

安南德什潘德

安南德什潘德在IT服務和產品開發方面擁有超過19年的經驗。他目前擔任VSquare Systems Pvt. Ltd.(VSquare)的高級分析和產品開發副總裁。他對數據科學和數據管理和分析的算法方法特別感興趣,並在2018年5月共同撰寫了一本名為《大數據人工智能》的書籍。

馬尼什·庫馬爾

馬尼什·庫馬爾在VSquare擔任技術和架構總監。他在為複雜業務問題提供技術解決方案方面擁有超過13年的經驗。他在Web應用程序開發、物聯網、大數據、雲技術和區塊鏈方面有豐富的工作經驗。除了這本書外,馬尼什還共同撰寫了三本書(《精通Hadoop 3》、《大數據人工智能》和《使用Apache Kafka構建流式應用程序》)。

維克拉姆·喬達里

維克拉姆·喬達里在VSquare擔任數據和高級分析總監。他在IT領域擁有超過10年的經驗。他是AWS和Google Cloud的認證架構師,並已完成多個使用Amazon Web Services和Google Cloud Platform的數據管道實施項目。憑藉在多個平台上實施數據管道的經驗,維克拉姆在創建可重用組件和加速器方面起著重要作用,從而降低成本和實施時間。

目錄大綱

  1. Overview of Artificial Intelligence and Google Cloud Platform
  2. Computing and Processing Using GCP Components
  3. Building Machine Learning Applications with XGBoost
  4. Using Cloud AutoML
  5. Building a Big Data Cloud Machine Learning Engine
  6. Building Smart Conversational Applications Using DialogFlow
  7. Understanding Cloud Tensor Processing Units
  8. Implement TensorFlow models using Cloud Machine Learning Engine
  9. Building Prediction Applications using Tensorflow Models
  10. Building an Artificial Intelligence application

目錄大綱(中文翻譯)

人工智慧和Google Cloud平台概述
使用GCP組件進行計算和處理
使用XGBoost構建機器學習應用程序
使用Cloud AutoML
構建大數據雲機器學習引擎
使用DialogFlow構建智能對話應用程序
了解Cloud Tensor Processing Units
使用Cloud Machine Learning Engine實現TensorFlow模型
使用TensorFlow模型構建預測應用程序
構建人工智慧應用程序