Hands-On Machine Learning on Google Cloud Platform: Implementing smart and efficient analytics using Cloud ML Engine

Giuseppe Ciaburro, V Kishore Ayyadevara, Alexis Perrier

  • 出版商: Packt Publishing
  • 出版日期: 2018-04-27
  • 定價: $1,520
  • 售價: 8.0$1,216
  • 語言: 英文
  • 頁數: 500
  • 裝訂: Paperback
  • ISBN: 1788393481
  • ISBN-13: 9781788393485
  • 相關分類: Google CloudMachine Learning
  • 立即出貨 (庫存=1)

買這商品的人也買了...

商品描述

Unleash Google's Cloud Platform to build, train and optimize machine learning models

Key Features

  • Get well versed in GCP pre-existing services to build your own smart models
  • A comprehensive guide covering aspects from data processing, analyzing to building and training ML models
  • A practical approach to produce your trained ML models and port them to your mobile for easy access

Book Description

Google Cloud Machine Learning Engine combines the services of Google Cloud Platform with the power and flexibility of TensorFlow. With this book, you will not only learn to build and train different complexities of machine learning models at scale but also host them in the cloud to make predictions.

This book is focused on making the most of the Google Machine Learning Platform for large datasets and complex problems. You will learn from scratch how to create powerful machine learning based applications for a wide variety of problems by leveraging different data services from the Google Cloud Platform. Applications include NLP, Speech to text, Reinforcement learning, Time series, recommender systems, image classification, video content inference and many other. We will implement a wide variety of deep learning use cases and also make extensive use of data related services comprising the Google Cloud Platform ecosystem such as Firebase, Storage APIs, Datalab and so forth. This will enable you to integrate Machine Learning and data processing features into your web and mobile applications.

By the end of this book, you will know the main difficulties that you may encounter and get appropriate strategies to overcome these difficulties and build efficient systems.

What you will learn

  • Use Google Cloud Platform to build data-based applications for dashboards, web, and mobile
  • Create, train and optimize deep learning models for various data science problems on big data
  • Learn how to leverage BigQuery to explore big datasets
  • Use Google's pre-trained TensorFlow models for NLP, image, video and much more
  • Create models and architectures for Time series, Reinforcement Learning, and generative models
  • Create, evaluate, and optimize TensorFlow and Keras models for a wide range of applications

Who This Book Is For

This book is for data scientists, machine learning developers and AI developers who want to learn Google Cloud Platform services to build machine learning applications. Since the interaction with the Google ML platform is mostly done via the command line, the reader is supposed to have some familiarity with the bash shell and Python scripting. Some understanding of machine learning and data science concepts will be handy

Table of Contents

  1. Setting up and Securing the Google Cloud Platform
  2. Interacting with Google Cloud Platform
  3. Google Cloud Storage
  4. Querying your data with BigQuery
  5. Transforming your data
  6. Essential Machine Learning
  7. Google Machine Learning APIs
  8. Creating Machine Learning Applications with Firebase
  9. Implementing a Feedforward network with TensorFlow and Keras
  10. Evaluating results with TensorBoard
  11. Optimizing your model with HyperTune
  12. Preventing Overfitting with regularization
  13. Beyond Feedforward networks
  14. Time series with LSTMs
  15. Reinforcement Learning with Tensorflow
  16. Generative neural networks
  17. Chatbots

商品描述(中文翻譯)

發揮 Google 的雲端平台,建立、訓練和優化機器學習模型

主要特點:
- 熟悉 GCP 的現有服務,建立自己的智能模型
- 全面指南,涵蓋從資料處理、分析到建立和訓練機器學習模型的各個方面
- 實用方法,將訓練好的機器學習模型移植到手機上,方便存取

書籍描述:
Google 雲端機器學習引擎結合了 Google 雲端平台的服務和 TensorFlow 的強大靈活性。通過本書,您不僅將學習如何建立和訓練不同複雜度的機器學習模型,還可以將其部署在雲端上進行預測。

本書專注於在大型數據集和複雜問題上充分利用 Google 機器學習平台。您將從頭開始學習如何通過利用 Google 雲端平台的不同數據服務,為各種問題創建強大的基於機器學習的應用。應用包括自然語言處理、語音轉文字、強化學習、時間序列、推薦系統、圖像分類、視頻內容推斷等等。我們將實現各種深度學習用例,並廣泛使用 Google 雲端平台生態系統中的數據相關服務,如 Firebase、存儲 API、Datalab 等等。這將使您能夠將機器學習和數據處理功能集成到您的網絡和移動應用程序中。

通過閱讀本書,您將了解可能遇到的主要困難,並獲得適當的策略來克服這些困難,構建高效的系統。

您將學到:
- 使用 Google 雲端平台為儀表板、網絡和移動應用程序建立基於數據的應用
- 在大數據上為各種數據科學問題創建、訓練和優化深度學習模型
- 學習如何利用 BigQuery 探索大型數據集
- 使用 Google 預訓練的 TensorFlow 模型進行自然語言處理、圖像、視頻等等
- 為時間序列、強化學習和生成模型創建模型和架構
- 創建、評估和優化廣泛應用於各種應用程序的 TensorFlow 和 Keras 模型

本書適合對象:
本書適合數據科學家、機器學習開發人員和人工智能開發人員,他們希望學習 Google 雲端平台服務以建立機器學習應用程序。由於與 Google ML 平台的互動主要通過命令行完成,讀者應該對 bash shell 和 Python 腳本有一定的熟悉。對機器學習和數據科學概念的一些理解將很有幫助。

目錄:
1. 設置和保護 Google 雲端平台
2. 與 Google 雲端平台互動
3. Google 雲端存儲
4. 使用 BigQuery 查詢數據
5. 轉換數據
6. 基本機器學習
7. Google 機器學習 API
8. 使用 Firebase 創建機器學習應用程序
9. 使用 TensorFlow 和 Keras 實現前饋網絡
10. 使用 TensorBoard 評估結果
11. 使用 HyperTune 優化模型
12. 使用正則化防止過擬合
13. 超越前饋網絡
14. 使用 LSTM 的時間序列
15. 使用 TensorFlow 的強化學習
16. 生成神經網絡
17. 聊天機器人