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Deep Learning with TensorFlow - Paperback, by Kapoor Amita; Gulli - Very Good
US $31.42
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Very Good
A book that does not look new and has been read but is in excellent condition. No obvious damage to the cover, with the dust jacket (if applicable) included for hard covers. No missing or damaged pages, no creases or tears, and no underlining/highlighting of text or writing in the margins. May be very minimal identifying marks on the inside cover. Very minimal wear and tear. See the sellerโs listing for full details and description of any imperfections.
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eBay item number:126560016018
Item specifics
- Condition
- Book Title
- Deep Learning with TensorFlow and Keras - Third Edition: Build an
- ISBN
- 9781803232911
- Publication Year
- 2022
- Type
- Textbook
- Format
- Trade Paperback
- Language
- English
- Subject Area
- Computers, Science
- Publication Name
- Deep Learning with TensorFlow and Keras : Build and Deploy Supervised, Unsupervised, Deep, and Reinforcement Learning Models
- Publisher
- Packt Publishing, The Limited
- Subject
- Machine Theory, Expert Systems, Computer Simulation, General
- Number of Pages
- 698 Pages
About this product
Product Identifiers
Publisher
Packt Publishing, The Limited
ISBN-10
1803232919
ISBN-13
9781803232911
eBay Product ID (ePID)
3058380900
Product Key Features
Subject
Machine Theory, Expert Systems, Computer Simulation, General
Publication Year
2022
Number of Pages
698 Pages
Publication Name
Deep Learning with TensorFlow and Keras : Build and Deploy Supervised, Unsupervised, Deep, and Reinforcement Learning Models
Language
English
Type
Textbook
Subject Area
Computers, Science
Format
Trade Paperback
Additional Product Features
Edition Number
3
Dewey Edition
23
Dewey Decimal
006.31
Synopsis
Build cutting edge machine and deep learning systems for the lab, production, and mobile devices. Purchase of the print or Kindle book includes a free eBook in PDF format. Key Features: Understand the fundamentals of deep learning and machine learning through clear explanations and extensive code samples Implement graph neural networks, transformers using Hugging Face and TensorFlow Hub, and joint and contrastive learning Learn cutting-edge machine and deep learning techniques Book Description: Deep Learning with TensorFlow and Keras teaches you neural networks and deep learning techniques using 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 2.x focuses on simplicity and ease of use, with updates like eager execution, intuitive higher-level APIs based on Keras, and flexible model building on any platform. This book uses the latest TF 2.0 features and libraries to present an overview of supervised and unsupervised machine learning models and provides a comprehensive analysis of deep learning and reinforcement learning models using practical examples for the cloud, mobile, and large production environments. This book also shows you how to create neural networks with TensorFlow, runs through popular algorithms (regression, convolutional neural networks (CNNs), transformers, GANs, recurrent neural networks (RNNs), natural language processing (NLP), and Graph Neural Networks (GNNs)), covers working example apps, and then dives into TF in production, TF mobile, and TensorFlow with AutoML. What You Will Learn: Learn how to use the popular GNNs with TensorFlow to carry out graph mining tasks Discover the world of transformers, from pretraining to fine-tuning to evaluating them Apply self-supervised learning to natural language processing, computer vision, and audio signal processing Combine probabilistic and deep learning models using TensorFlow Probability Train your models on the cloud and put TF to work in real environments Build machine learning and deep learning systems with TensorFlow 2.x and the Keras API Who this book is for: This hands-on machine learning book is for Python developers and data scientists who want to build machine learning and deep learning systems with TensorFlow. This book gives you the theory and practice required to use Keras, TensorFlow, and AutoML to build machine learning systems. Some machine learning knowledge would be useful. We don't assume TF knowledge.
LC Classification Number
Q325.73
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