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Can I read Deep Learning with TensorFlow 2.0 and Keras: Regression, ConvNets, GANs, RNNs, NLP & more with TF 2.0 and the Keras API on EtoBox?
Deep Learning with TensorFlow 2.0 and Keras: Regression, ConvNets, GANs, RNNs, NLP & more with TF 2.0 and the Keras API by Antonio Gulli, Amita Kapoor, Sujit Pal is a nonfiction available to read on EtoBox.
What is Deep Learning with TensorFlow 2.0 and Keras: Regression, ConvNets, GANs, RNNs, NLP & more with TF 2.0 and the Keras API about?
Build machine and deep learning systems with the newly released TensorFlow 2 and Keras for the lab, production, and mobile devices Key Features Introduces and then uses TensorFlow 2 and Keras right from the start Teaches key machine and deep learning techniques Understand the fundamentals of deep learning and machine learning through clear explanations and extensive code samples Book Description Deep Learning with TensorFlow 2 and Keras, Second Edition teaches neural networks and 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 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 (CNNs), GANs, RNNs, NLP), covers two working example apps, and then dives into TF in production, TF mobile, and using Te
Who reads Deep Learning with TensorFlow 2.0 and Keras: Regression, ConvNets, GANs, RNNs, NLP & more with TF 2.0 and the Keras API?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Antonio Gulli, Amita Kapoor, Sujit Pal
- Publisher
- Packt Publishing, Limited
- Published
- 2019
- Language
- EN
- ISBN
- 9781838823412
- Category
- nonfiction
- Subjects
- Science, Computer Science, Stem
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