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Deep Learning with TensorFlow Explore neural networks build intelligent systems
US $28.95
Approximately£22.78
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Located in: Potomac, Maryland, United States
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Estimated between Sat, 10 Aug and Tue, 13 Aug to 84606
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eBay item number:325269832430
Item specifics
- Condition
- Subject
- Web / Web Programming, Neural Networks, Internet / Application Development, Programming Languages / Python, Programming Languages / Javascript
- ISBN
- 9781788831109
- Publication Year
- 2018
- Type
- Textbook
- Format
- Trade Paperback
- Language
- English
- Subject Area
- Computers
- Publication Name
- Deep Learning with TensorFlow : Explore Neural Networks and Build Intelligent Systems with Python, 2nd Edition
- Publisher
- Packt Publishing, The Limited
- Item Length
- 3.6 in
- Item Width
- 3 in
- Number of Pages
- 484 Pages
About this product
Product Identifiers
Publisher
Packt Publishing, The Limited
ISBN-10
1788831101
ISBN-13
9781788831109
eBay Product ID (ePID)
27039629520
Product Key Features
Number of Pages
484 Pages
Language
English
Publication Name
Deep Learning with TensorFlow : Explore Neural Networks and Build Intelligent Systems with Python, 2nd Edition
Publication Year
2018
Subject
Web / Web Programming, Neural Networks, Internet / Application Development, Programming Languages / Python, Programming Languages / Javascript
Type
Textbook
Subject Area
Computers
Format
Trade Paperback
Dimensions
Item Length
3.6 in
Item Width
3 in
Additional Product Features
Edition Number
2
Intended Audience
Trade
Dewey Edition
23
Illustrated
Yes
Dewey Decimal
006.31
Table Of Content
Table of Contents Getting Started with Deep Learning A First Look at TensorFlow Feed-Forward Neural Networks with TensorFlow Convolutional Neural Networks Optimizing TensorFlow Autoencoders Recurrent Neural Networks Heterogeneous and Distributed Computing Advanced TensorFlow Programming Recommendation Systems using Factorization Machines Reinforcement Learning
Synopsis
This book introduces the core concepts of deep learning. Get implementation and research details on cutting-edge architectures and apply advanced concepts to your own projects. Develop your knowledge of deep neural networks through hands-on model building and examples of real-world data collection., Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of TensorFlow. Key Features Learn how to implement advanced techniques in deep learning with Google's brainchild, TensorFlow Explore deep neural networks and layers of data abstraction with the help of this comprehensive guide Gain real-world contextualization through some deep learning problems concerning research and application Book Description Deep learning is a branch of machine learning algorithms based on learning multiple levels of abstraction. Neural networks, which are at the core of deep learning, are being used in predictive analytics, computer vision, natural language processing, time series forecasting, and to perform a myriad of other complex tasks. This book is conceived for developers, data analysts, machine learning practitioners and deep learning enthusiasts who want to build powerful, robust, and accurate predictive models with the power of TensorFlow, combined with other open source Python libraries. Throughout the book, you'll learn how to develop deep learning applications for machine learning systems using Feedforward Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Autoencoders, and Factorization Machines. Discover how to attain deep learning programming on GPU in a distributed way. You'll come away with an in-depth knowledge of machine learning techniques and the skills to apply them to real-world projects. What you will learn Apply deep machine intelligence and GPU computing with TensorFlow Access public datasets and use TensorFlow to load, process, and transform the data Discover how to use the high-level TensorFlow API to build more powerful applications Use deep learning for scalable object detection and mobile computing Train machines quickly to learn from data by exploring reinforcement learning techniques Explore active areas of deep learning research and applications, Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of TensorFlow. Key Features Learn how to implement advanced techniques in deep learning with Google's brainchild, TensorFlow Explore deep neural networks and layers of data abstraction with the help of this comprehensive guide Gain real-world contextualization through some deep learning problems concerning research and application Book Description Deep learning is a branch of machine learning algorithms based on learning multiple levels of abstraction. Neural networks, which are at the core of deep learning, are being used in predictive analytics, computer vision, natural language processing, time series forecasting, and to perform a myriad of other complex tasks. This book is conceived for developers, data analysts, machine learning practitioners and deep learning enthusiasts who want to build powerful, robust, and accurate predictive models with the power of TensorFlow, combined with other open source Python libraries. Throughout the book, you'll learn how to develop deep learning applications for machine learning systems using Feedforward Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Autoencoders, and Factorization Machines. Discover how to attain deep learning programming on GPU in a distributed way. You'll come away with an in-depth knowledge of machine learning techniques and the skills to apply them to real-world projects. What you will learn Apply deep machine intelligence and GPU computing with TensorFlow Access public datasets and use TensorFlow to load, process, and transform the data Discover how to use the high-level TensorFlow API to build more powerful applications Use deep learning for scalable object detection and mobile computing Train machines quickly to learn from data by exploring reinforcement learning techniques Explore active areas of deep learning research and applications Who this book is for The book is for people interested in machine learning and machine intelligence. A rudimentary level of programming in one language is assumed, as is a basic familiarity with computer science techniques and technologies, including a basic awareness of computer hardware and algorithms. Some competence in mathematics is needed to the level of elementary linear algebra and calculus.
LC Classification Number
Q325.5.Z3 2018
Item description from the seller
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eBay item number:325269832430
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Potomac, Maryland, United States
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