Build machine and deep learning systems with the newly released TensorFlow 2.0 and Keras for the lab, production, and mobile devices
Key Features
- Introduces and then uses TensorFlow 2.0 and Keras right from the start
- Teaches key machine and deep learning techniques
- Covers theory and practice with clear explanations and extensive code samples
Book Description
Deep Learning with TensorFlow 2.0 and Keras – Second Edition teaches deep learning techniques alongside TensorFlow (TF) and Keras. You’ll learn how to write deep learning applications in the most powerful, popular, and scalable machine learning stack available.
TensorFlow is the machine learning library of choice for professional applications, while Keras offers a simple and powerful Python API for accessing TensorFlow. TensorFlow 2.0 provides full Keras integration, making advanced machine learning easier and more convenient than ever before.
This book also introduces neural networks with TensorFlow, runs through the main applications (regression, ConvNets, GANs, RNNs, NLP), covers two working example apps, and then dives into TF in production, TF mobile, and using TensorFlow with AutoML.
What you will learn
- Build machine learning and deep learning systems with TensorFlow 2.0 and the Keras API
- Regression – the most widely used approach to machine learning
- ConvNets – convolutional neural networks, essential for deep learning systems such as image classifiers
- GANs – generative adversarial networks that use deep learning techniques to create new data that fits with existing patterns
- RNNs – recurrent neural networks that can process sequences of input intelligently, using one part of a sequence to correctly interpret another
- NLP – apply deep learning to natural human language – interpreting natural language texts to produce an appropriate response
- TF and Cloud in production
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