Hands-On Machine Learning on Google Cloud Platform

English | 2018 | ISBN: 978-1788393485 | 500 Pages | EPUB | 24 MB

Machine Learning on Google Cloud Platform: A hands-on guide to implementing smart and efficient analytics using Cloud ML engine
Unleash Google’s Cloud Platform to build, train and optimize machine learning models
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