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Deep Learning mit TensorFlow Erkunden Sie neuronale Netze intelligente Systeme bauen -

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Deep Learning with TensorFlow Explore neural networks build intelligent systems
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Artikelzustand
Neu: Neues, ungelesenes, ungebrauchtes Buch in makellosem Zustand ohne fehlende oder beschädigte ...
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
Author
Rezaul Karim, Giancarlo Zaccone
Publisher
Packt Publishing, The Limited
Item Length
3.6 in
Item Width
3 in
Number of Pages
484 Pages

Über dieses Produkt

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
Author
Rezaul Karim, Giancarlo Zaccone
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

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Great Box had over 160.00 in cards 2 bucks and above with 6 triomes and 3 of them were showcase boarderless.. No Ozolith n the topper was just baby Godzilla but man it was a fun Boaz thanks…
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