Hands-On Machine Learning on Google Cloud Platform

Unleash Google's Cloud Platform to build, train and optimize machine learning models

Hands-On Machine Learning on Google Cloud Platform

Giuseppe Ciaburro, V Kishore Ayyadevara, Alexis Perrier

Unleash Google's Cloud Platform to build, train and optimize machine learning models
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Book Details

ISBN 139781788393485
Paperback500 pages

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.

Table of Contents

Chapter 8: Creating ML Applications with Firebase
Chapter 9: Neural Networks with TensorFlow and Keras
Chapter 10: Evaluating Results with TensorBoard
Chapter 11: Optimizing the Model through Hyperparameter Tuning
Chapter 12: Preventing Overfitting with Regularization

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

Authors

Table of Contents

Chapter 8: Creating ML Applications with Firebase
Chapter 9: Neural Networks with TensorFlow and Keras
Chapter 10: Evaluating Results with TensorBoard
Chapter 11: Optimizing the Model through Hyperparameter Tuning
Chapter 12: Preventing Overfitting with Regularization

Book Details

ISBN 139781788393485
Paperback500 pages
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