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Giuseppe Ciaburro - Hands-On Machine Learning on Google Cloud Platform

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Unleash Googles Cloud Platform to build, train and optimize machine learning models

About This Book

  • 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

      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

      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 Googles 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

      In Detail

      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.

      Style and approach

      An easy-to-follow step by step guide which will help you get to the grips with real-world applications of Google Cloud Machine Learning.

  • Giuseppe Ciaburro: author's other books


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    Hands-On Machine Learning on Google Cloud Platform Implementing smart and - photo 1
    Hands-On Machine Learning on Google Cloud Platform
    Implementing smart and efficient analytics using Cloud ML Engine
    Giuseppe Ciaburro
    V Kishore Ayyadevara
    Alexis Perrier
    BIRMINGHAM - MUMBAI Hands-On Machine Learning on Google Cloud Platform - photo 2
    BIRMINGHAM - MUMBAI
    Hands-On Machine Learning on Google Cloud Platform

    Copyright 2018 Packt Publishing

    All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

    Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the authors, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book.

    Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

    Commissioning Editor: Sunith Shetty
    Acquisition Editor: Tushar Gupta
    Content Development Editor: Cheryl Dsa
    Technical Editor: Dinesh Pawar
    Copy Editor: Vikrant Phadkay
    Project Coordinator: Nidhi Joshi
    Proofreader: Safis Editing
    Indexer: Mariammal Chettiyar
    Graphics: Tania Dutta
    Production Coordinator: Arvindkumar Gupta

    First published: April 2018

    Production reference: 1260418

    Published by Packt Publishing Ltd.
    Livery Place
    35 Livery Street
    Birmingham
    B3 2PB, UK.

    ISBN 978-1-78839-348-5

    www.packtpub.com

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    Contributors
    About the authors

    Giuseppe Ciaburro holds a PhD in environmental technical physics and two master's degrees. His research is on machine learning applications in the study of urban sound environments. He works at Built Environment Control Laboratory, Universit degli Studi della Campania Luigi Vanvitelli (Italy). He has over 15 years' experience in programming Python, R, and MATLAB, first in the field of combustion, and then in acoustics and noise control. He has several publications to his credit .

    V Kishore Ayyadevara has over 9 years' experience of using analytics to solve business problems and setting up analytical work streams through his work at American Express, Amazon, and, more recently, a retail analytics consulting startup. He has an MBA from IIM Calcutta and is also an electronics and communications engineer. He has worked in credit risk analytics, supply chain analytics, and consulting for multiple FMCG companies to identify ways to improve their profitability.

    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.

    About the reviewers

    Mikhail Berlyant is a data warehousing veteran. He has been a data developer since the late 1970s. Since 2000, he has led data systems, data mining, and data warehouse teams at Yahoo! and Myspace.

    He is a Google Cloud expert and senior VP of Technology, at Viant Inc., a people-based advertising tech company that enables marketers to plan, execute, and measure their digital media investments through a cloud-based platform. At Viant, he led the migration of a petabyte-sized data warehouse to Google Cloud. He is currently focusing on self-serve/productivity tools for BigQuery/GCP.

    I'd like to say thanks to my beautiful wife, Svetlana, for supporting me in all my endeavors.

    Sanket Thodge is an entrepreneur by profession in Pune, India. He is an author of Cloud Analytics with Google Cloud Platform. He founded Pi R Square Digital Solutions. With expertise as a Hadoop developer, he has explored the cloud, IoT, machine learning, and blockchain. He has also applied for a patent in IoT and has worked with numerous startups and MNCs, providing consultancy, architecture building, development, and corporate training across the globe.

    Antonio Gulli is a transformational software executive and business leader with a passion for establishing and managing global technological talent for innovation and execution. He is an expert in search engines, online services, machine learning, and so on. Currently, he is a site lead and director of cloud at Google Warsaw, driving European efforts for serverless, Kubernetes, and Google Cloud UX. Antonio has filed for 20+ patents, published multiple academic papers, and served as a senior PC member in multiple international conferences.

    Chirag Nayyar is helping organizations to migrate their workload from on-premise to the public cloud. He has experience in web app migration, SAP workload on the cloud, and EDW. He is c urrently working at Cloud Kinetics Technology Solutions. He holds a wide range of certifications from all major public cloud platforms. He also runs meetups and is a regular speaker at various cloud events.

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