Search icon
Subscription
0
Cart icon
Close icon
You have no products in your basket yet
Save more on your purchases!
Savings automatically calculated. No voucher code required
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletters
Free Learning
Arrow right icon
Hands-On Machine Learning on Google Cloud Platform

You're reading from  Hands-On Machine Learning on Google Cloud Platform

Product type Book
Published in Apr 2018
Publisher Packt
ISBN-13 9781788393485
Pages 500 pages
Edition 1st Edition
Languages
Authors (3):
Giuseppe Ciaburro Giuseppe Ciaburro
Profile icon Giuseppe Ciaburro
V Kishore Ayyadevara V Kishore Ayyadevara
Profile icon V Kishore Ayyadevara
Alexis Perrier Alexis Perrier
Profile icon Alexis Perrier
View More author details

Table of Contents (18) Chapters

Preface 1. Introducing the Google Cloud Platform 2. Google Compute Engine 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 ML Applications with Firebase 9. Neural Networks with TensorFlow and Keras 10. Evaluating Results with TensorBoard 11. Optimizing the Model through Hyperparameter Tuning 12. Preventing Overfitting with Regularization 13. Beyond Feedforward Networks – CNN and RNN 14. Time Series with LSTMs 15. Reinforcement Learning 16. Generative Neural Networks 17. Chatbots

Introducing the GCP

The first cloud computing service dates back to 15 years ago, when, in July 2002, Amazon launched the AWS platform to expose technology and product data from Amazon and its affiliates, enabling developers to build innovative and entrepreneurial applications on their own. In 2006, AWS was relaunched as the EC2.

The early start of AWS gave Amazon a lead in cloud computing, one that has never faltered since. Competitors were slow to counteract and launch their own offers. The first alternative to the AWS cloud services from a major company came with the Google App Engine launched in April 2008 as a PaaS service for developing and hosting web applications. The GCP was thus born. Microsoft and IBM followed, with the Windows Azure platform launched in February 2010 and LotusLive in January 2009.

Google didn’t enter the IaaS market until much later. In 2013, Google released the Compute Engine to the general public with enterprise service-level agreements (SLA).

Mapping the GCP

With over 40 different IaaS, PaaS, and SaaS services, the GCP ecosystem is rich and complex. These services can be grouped into six different categories:

  • Hosting and computation
  • Storage and databases
  • Networking
  • ML
  • Identity and security
  • Resource management and monitoring

In the following section, we learn how to set up and manage a single VM instance on Google Compute Engine. But, before that, we need to create our account.

You have been reading a chapter from
Hands-On Machine Learning on Google Cloud Platform
Published in: Apr 2018 Publisher: Packt ISBN-13: 9781788393485
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $15.99/month. Cancel anytime}