000 03415cam a2200289zu 4500
001 88900543
003 FRCYB88900543
005 20250107233403.0
006 m o d
007 cr un
008 250108s2020 fr | o|||||0|0|||eng d
020 _a9781800201217
035 _aFRCYB88900543
040 _aFR-PaCSA
_ben
_c
_erda
100 1 _aChadha, Harveen Singh
245 0 1 _aThe Applied TensorFlow and Keras Workshop
_c['Chadha, Harveen Singh', 'Capelo, Luis']
264 1 _bPackt Publishing
_c2020
300 _a p.
336 _btxt
_2rdacontent
337 _bc
_2rdamdedia
338 _bc
_2rdacarrier
650 0 _a
700 0 _aChadha, Harveen Singh
700 0 _aCapelo, Luis
856 4 0 _2Cyberlibris
_uhttps://international.scholarvox.com/netsen/book/88900543
_qtext/html
_a
520 _aCut through the noise and get real results with this workshop for beginners. Use a project-based approach to exploring machine learning with TensorFlow and Keras. Key Features Understand the nuances of setting up a deep learning programming environment Gain insights into the common components of a neural network and its essential operations Get to grips with deploying a machine learning model as an interactive web application with Flask Book Description Machine learning gives computers the ability to learn like humans. It is becoming increasingly transformational to businesses in many forms, and a key skill to learn to prepare for the future digital economy. As a beginner, you'll unlock a world of opportunities by learning the techniques you need to contribute to the domains of machine learning, deep learning, and modern data analysis using the latest cutting-edge tools. The Applied TensorFlow and Keras Workshop begins by showing you how neural networks work. After you've understood the basics, you will train a few networks by altering their hyperparameters. To build on your skills, you'll learn how to select the most appropriate model to solve the problem in hand. While tackling advanced concepts, you'll discover how to assemble a deep learning system by bringing together all the essential elements necessary for building a basic deep learning system - data, model, and prediction. Finally, you'll explore ways to evaluate the performance of your model, and improve it using techniques such as model evaluation and hyperparameter optimization. By the end of this book, you'll have learned how to build a Bitcoin app that predicts future prices, and be able to build your own models for other projects. What you will learn Familiarize yourself with the components of a neural network Understand the different types of problems that can be solved using neural networks Explore different ways to select the right architecture for your model Make predictions with a trained model using TensorBoard Discover the components of Keras and ways to leverage its features in your model Explore how you can deal with new data by learning ways to retrain your model Who this book is for If you are a data scientist or a machine learning and deep learning enthusiast, who is looking to design, train, and deploy TensorFlow and Keras models into real-world applications, then this workshop is for you. Knowledge of computer science and machine learning concepts and experience in analyzing data will help you to understand the topics explained in this book with ease.
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