Docker on Windows: From 101 to production with Docker on Windows, 2nd Edition - Couverture souple

Stoneman, Elton

Couverture souple

ISBN 10 : 1789617375 ISBN 13 : 9781789617375

Editeur : Packt Publishing, 2019

Synopsis

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

A propos du livre

À propos de l?auteur

Giuseppe Ciaburro holds a PhD in environmental technical physics, along with two master's degrees. His research was focused on machine learning applications in the study of urban sound environments. He works at the Built Environment Control Laboratory at the Università degli Studi della Campania Luigi Vanvitelli, Italy. He has over 15 years' professional 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.

Détails de l'édition

• Éditeur: Packt Publishing
• Date d'édition: 2019
• Langue: anglais
• ISBN 10: 1789617375
• ISBN 13: 9781789617375
• Reliure: Broché
• Numéro d'édition: 2
• Nombre de pages: 428
• Coordonnées du fabricant: non disponible
• Personne responsable: non disponible