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

Product typeBook

Published inApr 2018

PublisherPackt

ISBN-139781788393485

Edition1st Edition

Tools

Google Cloud Platform

Concepts

Machine Learning

Authors (3):

Giuseppe Ciaburro

V Kishore Ayyadevara

Alexis Perrier

View More author details

Many excellent articles on the GCP use for big data can be found on the Google big data blog at https://cloud.google.com/blog/big-data/.
What are the GCP services? Reto Meier, software engineer at Google, describes the different Google Cloud services in a simple way (for more information, see https://hackernoon.com/what-are-the-google-cloud-platform-gcp-services-285f1988957a). This is very useful for grasping the diversity of the GCP services.
An Annotated History of Google’s Cloud Platform is another post by Reto Meier on the history of the GCP. You can find it at: https://medium.com/@retomeier/an-annotated-history-of-googles-cloud-platform-90b90f948920. It starts with the bullet point: Pre 2008 — Computers invented. Google Founded.... A much more detailed timeline of the GCP is available on Crunchbase at https://www.crunchbase.com/organization/google-cloud-platform/timeline#/timeline/index.
The evolution of computing power, also known as Moore's law, is available at http://www.cs.columbia.edu/~sedwards/classes/2012/3827-spring/advanced-arch-2011.pdf, and a more recent version where the seven most recent data points are all NVIDIA GPUs is available at https://en.wikipedia.org/wiki/Moore%27s_law#/media/File:Moore%27s_Law_over_120_Years.png.
For more on the pricing war of the three main cloud platforms, see this article: Cloud Pricing Trends: Get the White Paper, Rightscale, 2013, at https://www.rightscale.com/lp/cloud-pricing-trends-white-paper.
A good article on Supercomputing vs. Cloud Computing by David Stepania can be found at https://www.linkedin.com/pulse/supercomputing-vs-cloud-computing-david-stepania/.

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Authors (3)

Giuseppe Ciaburro

Giuseppe Ciaburro holds a PhD and two master's degrees. He works at the Built Environment Control Laboratory - Università degli Studi della Campania "Luigi Vanvitelli". He has over 25 years of work experience in programming, first in the field of combustion and then in acoustics and noise control. His core programming knowledge is in MATLAB, Python and R. As an expert in AI applications to acoustics and noise control problems, Giuseppe has wide experience in researching and teaching. He has several publications to his credit: monographs, scientific journals, and thematic conferences. He was recently included in the world's top 2% scientists list by Stanford University (2022).
Read more about Giuseppe Ciaburro

V Kishore Ayyadevara

V Kishore Ayyadevara leads a team focused on using AI to solve problems in the healthcare space. He has 10 years' experience in data science, solving problems to improve customer experience in leading technology companies. In his current role, he is responsible for developing a variety of cutting edge analytical solutions that have an impact at scale while building strong technical teams. Prior to this, Kishore authored three books — Pro Machine Learning Algorithms, Hands-on Machine Learning with Google Cloud Platform, and SciPy Recipes. Kishore is an active learner with keen interest in identifying problems that can be solved using data, simplifying the complexity and in transferring techniques across domains to achieve quantifiable results.
Read more about V Kishore Ayyadevara

Alexis Perrier

Alexis Perrier is a data science consultant with experience in signal processing and stochastic algorithms. He holds a master's in mathematics from Universit Pierre et Marie Curie Paris VI and a PhD in signal processing from Tlcom ParisTech. He is actively involved in the DC data science community. He is also an avid book lover and proud owner of a real chalk blackboard, where he regularly shares his fascination of mathematical equations with his kids.
Read more about Alexis Perrier

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