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Capelo L. Beginning Application Development with TensorFlow and Keras
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Packt Publishing, 2018. — 148 p. — ISBN: 978-1789537291.Key FeaturesFocus on neural network and its essential operations
Prepare data for a deep learning model and deploy it as an interactive web application, with Flask and a HTTP API
Use Keras, a TensorFlow abstraction libraryBook DescriptionWith this book, you'll learn how to train, evaluate and deploy Tensorflow and Keras models as real-world web applications. After a hands-on introduction, you'll use a sample model to explore the details of deep learning, selecting the right layers that can solve a given problem. By the end of the course, you'll build a Bitcoin application that predicts the future price, based on historic, and freely available information.This book will also provide you with a blueprint for how to build an application that generates predictions using a deep learning model. From there, you can continue to improve our example model — either by adding more data, computing more features, or changing its architecture — continuously increasing its prediction accuracy, or create a completely new model, changing the core components of the application as you see fit.What you will learnSet up a deep learning programming environment
Explore the common components of a neural network and its essential operations
Prepare data for a deep learning model
Deploy model as an interactive web application, with Flask and a HTTP API
Use Keras, a TensorFlow abstraction library
Explore the types of problems addressed by neural networksWho This Book Is ForThis course is ideal for experienced developers, analysts, or a data scientists, who want to develop applications using TensorFlow and Keras. This rapid hands-on course quickly shows you how to get to grips with TensorFlow in the context of real-world application development. We assume that you are familiar with Python and have a basic knowledge of web application development. If you have a background in linear algebra, probability, and statistics, you will easily grasp concepts that are discussed in the course.
Prepare data for a deep learning model and deploy it as an interactive web application, with Flask and a HTTP API
Use Keras, a TensorFlow abstraction libraryBook DescriptionWith this book, you'll learn how to train, evaluate and deploy Tensorflow and Keras models as real-world web applications. After a hands-on introduction, you'll use a sample model to explore the details of deep learning, selecting the right layers that can solve a given problem. By the end of the course, you'll build a Bitcoin application that predicts the future price, based on historic, and freely available information.This book will also provide you with a blueprint for how to build an application that generates predictions using a deep learning model. From there, you can continue to improve our example model — either by adding more data, computing more features, or changing its architecture — continuously increasing its prediction accuracy, or create a completely new model, changing the core components of the application as you see fit.What you will learnSet up a deep learning programming environment
Explore the common components of a neural network and its essential operations
Prepare data for a deep learning model
Deploy model as an interactive web application, with Flask and a HTTP API
Use Keras, a TensorFlow abstraction library
Explore the types of problems addressed by neural networksWho This Book Is ForThis course is ideal for experienced developers, analysts, or a data scientists, who want to develop applications using TensorFlow and Keras. This rapid hands-on course quickly shows you how to get to grips with TensorFlow in the context of real-world application development. We assume that you are familiar with Python and have a basic knowledge of web application development. If you have a background in linear algebra, probability, and statistics, you will easily grasp concepts that are discussed in the course.
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