Building Machine Learning and Deep Learning Models on Google Cloud Platform: A Comprehensive Guide for Beginners

Bisong, Ekaba Ononse

  • 出版商: Apress
  • 出版日期: 2019-09-28
  • 定價: $1,575
  • 售價: 9.0$1,418
  • 語言: 英文
  • 頁數: 580
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1484244699
  • ISBN-13: 9781484244692
  • 相關分類: Google CloudMachine LearningDeepLearning
  • 立即出貨 (庫存=1)



So you want to build learning models from the ground up, but find the rapidly changing world of machine learning and deep learning overwhelming and confusing, and you don't have a clue where to start. This book is your "one-stop shop" to understand the theoretical foundations and the practical steps to leverage machine learning and deep learning.

You will learn about machine learning tools and techniques used to predict or classify events based on a set of interactions between variables known as features or attributes in a particular dataset. And you will learn how deep learning extends machine learning algorithms of neural networks for learning complex tasks which are difficult for computers to perform such as recognizing faces and understanding languages. And you will know how the cloud is made up large sets of computers networked together in groups called data centers that are distributed across geographic locations and managed by companies such as Google, Microsoft, Amazon, and IBM and made available for public use by enterprises and personal users.

This book is a beginner's comprehensive guide for building learning models to address complex use cases using machine learning and deep learning principles and techniques while leveraging the computational resources and artificial intelligence (AI) capabilities of the Google Cloud Platform at a reasonable cost.

Building Machine Learning and Deep Learning Models on Google Cloud Platform is divided into six parts that cover the foundations of machine learning and deep learning, the concept of data science and cloud services, programming for data science and machine learning and deep learning using the Python stack, Google Cloud Platform infrastructure and products, and an end-to-end machine/deep learning project on the Google Cloud Platform.

What You'll Learn


  • Understand the principles and fundamentals of machine learning and deep learning, the algorithms, how to use them, when to use them, and how to interpret your results
  • Know the programming concepts relevant to machine and deep learning design and development using the Python stack
  • Build and interpret machine and deep learning models
  • Use Google Cloud Platform tools and services to develop and deploy machine learning and deep learning products
  • Be aware of the different facets and design choices to consider when modeling a learning problem
  • Productionalize machine learning models into software products









Who This Book Is For

Beginning software application developers. Experts in machine learning and deep learning design and modeling can benefit from this book as a refresher.




這本書是一本初學者的綜合指南,教你如何使用機器學習和深度學習原理和技術來解決複雜的使用案例,同時利用Google Cloud Platform的計算資源和人工智能(AI)能力,以合理的成本。

《在Google Cloud Platform上建立機器學習和深度學習模型》分為六個部分,涵蓋機器學習和深度學習的基礎知識、數據科學和雲服務的概念、使用Python堆棧進行數據科學和機器學習和深度學習的編程、Google Cloud Platform基礎設施和產品,以及在Google Cloud Platform上進行端到端機器/深度學習項目。


- 理解機器學習和深度學習的原理和基礎知識,算法的使用方法、使用時機以及如何解釋結果
- 熟悉與機器和深度學習設計和開發相關的編程概念,使用Python堆棧
- 構建和解釋機器和深度學習模型
- 使用Google Cloud Platform工具和服務開發和部署機器學習和深度學習產品
- 瞭解在建模學習問題時需要考慮的不同方面和設計選擇
- 將機器學習模型投入生產,成為軟件產品


- 初級軟件應用開發人員
- 機器學習和深度學習設計和建模專家,可以作為複習資料使用。


Ekaba Bisong is a data scientist at Pythian, a big data analytics company headquartered in Ottawa, Canada. He is also a master degree graduate student in the School of Computer Science at Carleton University with a research focus on learning systems (encompassing learning automata and reinforcement learning), machine learning, and deep learning. He is a Google Certified Professional Data Engineer. Teaching is his passion, and this book reflects his teaching philosophy of imparting knowledge in a way that incrementally takes the learner from the point of knowing nothing to the place where they can function as experts in the subject matter.


Ekaba Bisong是加拿大渥太華的大數據分析公司Pythian的數據科學家。他也是卡爾頓大學計算機科學學院的碩士研究生,研究方向包括學習系統(包括學習自動機和強化學習)、機器學習和深度學習。他是Google認證的專業數據工程師。教學是他的熱情所在,這本書體現了他的教學理念,以一種漸進的方式傳授知識,使學習者從一無所知逐步成為該領域的專家。