Book Image

Hands-On Machine Learning on Google Cloud Platform

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

Hands-On Machine Learning on Google Cloud Platform

By: Giuseppe Ciaburro, V Kishore Ayyadevara, 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)
8
Creating ML Applications with Firebase

Speech-to-text API

The Google Cloud Speech API enables developers to convert audio to text, by applying powerful neural network models in an easy-to-use API. The API recognizes over 110 languages and variants. One can transcribe the text of users dictating to an application's microphone, enable command-and-control through voice, or transcribe audio files, among many use cases.

In order to enable the speech to text API, search for it in the console, as follows:

In the resulting web page, enable the API, as follows:

Similar to the APIs mentioned in the previous sections, credentials obtained for one API can be replicated for the other Google APIs. So, we don't have to create credentials separately for the speech to text API.

Once the API is enabled, let's start the Cloud Shell and Datalab, as we did in the previous sections.

In the following code, we transcribe...