Book Image

Hands-On Machine Learning on Google Cloud Platform

By : Giuseppe Ciaburro, V Kishore Ayyadevara, Alexis Perrier
Book Image

Hands-On Machine Learning on Google Cloud Platform

By: Giuseppe Ciaburro, V Kishore Ayyadevara, Alexis Perrier

Overview of this book

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 (18 chapters)
Creating ML Applications with Firebase


On June 1, 2016, Google launched the Magenta project, a research project that aims to allow the creation of art and music in an autonomous way through the use of AI. Based on the TensorFlow platform, Magenta aims to publish code in open source mode on GitHub to allow developers to achieve increasingly striking and advanced results.

The project is a brainchild of the Google Brain team, a deep learning AI research team at Google. It combines open-ended machine learning research with system engineering and Google-scale computing resources.

The Magenta project has set itself two ambitious goals: to develop machine learning for art and music, and to build a community of people interested in this topic. Machine learning has long been used in different contexts, in particular for speech recognition and translation of languages. Magenta was created to concentrate activity on...