Hands-On Deep Learning with TensorFlow : Uncover what is underneath your data!
Language: English
Published by Packt Publishing, 2017
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 58.13
Quantity: 1 available
Add to basketItem description from seller
nach der Bestellung gedruckt Neuware - Printed after ordering - This book is your guide to exploring the possibilities in the field of deep learning, making use of Google's TensorFlow. You will learn about convolutional neural networks, and logistic regression while training models for deep learning to gain key insights into your data.Key Features: Explore various possibilities with deep learning and gain amazing insights from data using Google's brainchild-- TensorFlow Want to learn what more can be done with deep learning Explore various neural networks with the help of this comprehensive guide Rich in concepts, advanced guide on deep learning that will give you background to innovate in your environmentBook Description:Dan Van Boxel's Deep Learning with TensorFlow is based on Dan's best-selling TensorFlow video course. With deep learning going mainstream, making sense of data and getting accurate results using deep networks is possible. Dan Van Boxel will be your guide to exploring the possibilities with deep learning; he will enable you to understand data like never before. With the efficiency and simplicity of TensorFlow, you will be able to process your data and gain insights that will change how you look at data.With Dan's guidance, you will dig deeper into the hidden layers of abstraction using raw data. Dan then shows you various complex algorithms for deep learning and various examples that use these deep neural networks. You will also learn how to train your machine to craft new features to make sense of deeper layers of data.In this book, Dan shares his knowledge across topics such as logistic regression, convolutional neural networks, recurrent neural networks, training deep networks, and high level interfaces. With the help of novel practical examples, you will become an ace at advanced multilayer networks, image recognition, and beyond.What You Will Learn: Set up your computing environment and install TensorFlow Build simple TensorFlow graphs for everyday computations Apply logistic regression for classification with TensorFlow Design and train a multilayer neural network with TensorFlow Intuitively understand convolutional neural networks for image recognition Bootstrap a neural network from simple to more accurate models See how to use TensorFlow with other types of networks Program networks with SciKit-Flow, a high-level interface to TensorFlowWho this book is for:If you are a data scientist who performs machine learning on a regular basis, are familiar with deep neural networks, and now want to gain expertise in working with convoluted neural networks, then this book is for you. Some familiarity with C++ or Python is assumed.Table of Contents Getting Started Deep Neural Networks Convolutional Neural Networks Recurrent Neural Networks Wrapping Up.…
Seller Inventory # 9781787282773
- Title
- Hands-On Deep Learning with TensorFlow : Uncover what is underneath your data!
- Author
- Dan van Boxel
- Publisher
- Packt Publishing
- Publication year
- 2017
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 1787282775
- ISBN 13
- 9781787282773
- Item weight
- 338 grams
- Dimensions
- 235x191x10 mm
This book is your guide to exploring the possibilities in the field of deep learning, making use of Google's TensorFlow. You will learn about convolutional neural networks, and logistic regression while training models for deep learning to gain key insights into your data.
Key Features:
- Explore various possibilities with deep learning and gain amazing insights from data using Google's brainchild-- TensorFlow
- Want to learn what more can be done with deep learning? Explore various neural networks with the help of this comprehensive guide
- Rich in concepts, advanced guide on deep learning that will give you background to innovate in your environment
Book Description:
Dan Van Boxel's Deep Learning with TensorFlow is based on Dan's best-selling TensorFlow video course. With deep learning going mainstream, making sense of data and getting accurate results using deep networks is possible. Dan Van Boxel will be your guide to exploring the possibilities with deep learning; he will enable you to understand data like never before. With the efficiency and simplicity of TensorFlow, you will be able to process your data and gain insights that will change how you look at data.
With Dan's guidance, you will dig deeper into the hidden layers of abstraction using raw data. Dan then shows you various complex algorithms for deep learning and various examples that use these deep neural networks. You will also learn how to train your machine to craft new features to make sense of deeper layers of data.
In this book, Dan shares his knowledge across topics such as logistic regression, convolutional neural networks, recurrent neural networks, training deep networks, and high level interfaces. With the help of novel practical examples, you will become an ace at advanced multilayer networks, image recognition, and beyond.
What You Will Learn:
- Set up your computing environment and install TensorFlow
- Build simple TensorFlow graphs for everyday computations
- Apply logistic regression for classification with TensorFlow
- Design and train a multilayer neural network with TensorFlow
- Intuitively understand convolutional neural networks for image recognition
- Bootstrap a neural network from simple to more accurate models
- See how to use TensorFlow with other types of networks
- Program networks with SciKit-Flow, a high-level interface to TensorFlow
Who this book is for:
If you are a data scientist who performs machine learning on a regular basis, are familiar with deep neural networks, and now want to gain expertise in working with convoluted neural networks, then this book is for you. Some familiarity with C++ or Python is assumed.
Table of Contents
- Getting Started
- Deep Neural Networks
- Convolutional Neural Networks
- Recurrent Neural Networks
- Wrapping Up
"Synopsis" may belong to another edition of this title.
About the Author
"About the title" may belong to another edition of this title.
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