Beginning Application Development with TensorFlow and Keras
Book information
Description
You need much more than imagination to predict earthquakes and detect brain cancer cells. Become an expert in designing and deploying TensorFlow and Keras models, and generate insightful predictions with the power of deep learning. About This BookCover the basics of neural networks and choose the right model architectureMake predictions with a trained model and get to grips with TensorBoardEvaluate metrics and techniques and deploy a model as a web applicationWho This Book Is For This book 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 book. What You Will LearnSet up a deep learning programming environmentExplore the common components of a neural network and its essential operationsPrepare data for a deep learning model- Deploy model as an interactive web application, with Flask and a HTTP APIUse Keras, a TensorFlow abstraction libraryExplore the types of problems addressed by neural networksIn Detail With 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 book, you’ll build a Bitcoin application that predicts the future price, based on historic, and freely available information. Style and approach This step-by-step guide will explore common, and not so common, deep neural networks and show how these can be exploited in the real world with complex raw data. With the help of practical examples, you will learn how to implement different types of neural nets to build smart applications related to text, speech, and image data processing. Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.
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