Google Cloud ML Engine combines the services of Google Cloud Platform with the power and flexibility of TensorFlow. With this book, you will not only learn how to build and train different complexities of machine learning models at scale, but also to 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 how to create powerful machine-learning-based applications from scratch 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 others. We will implement a wide variety of deep learning use cases and will 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 be aware of the main difficulties that you may encounter, and be familiar with appropriate strategies to overcome these difficulties and build efficient systems.
