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Hands-On Machine Learning on Google Cloud Platform

Hands-On Machine Learning on Google Cloud Platform

By : Perrier, Giuseppe Ciaburro, V Kishore Ayyadevara
3.5 (2)
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Hands-On Machine Learning on Google Cloud Platform

Hands-On Machine Learning on Google Cloud Platform

3.5 (2)
By: Perrier, Giuseppe Ciaburro, V Kishore Ayyadevara

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)
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8
Creating ML Applications with Firebase

Handwriting Recognition using CNN and TensorFlow

Handwriting Recognition (HWR) is a very commonly used procedure in modern technology. An image of written text can be detected offline from a piece of paper by optical scanning (optical character recognition or OCR) or intelligent word recognition. Alternatively, pen tip movements can be detected online (for example, from a pen computer surface, a task that is generally easier since there are more clues available).

Technically, recognition of handwriting is the ability of a computer to receive and interpret a handwritten intelligible input from sources such as paper documents, photos, touchscreens, and other devices. HWR is performed through various techniques that generally require OCR. However, a complete script recognition system also manages formatting, carries out correct character segmentation, and finds the most plausible...

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