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Python Deep Learning

Develop Your First Neural Network In Python Using TensorFlow, Keras, And PyTorch - Step-by-Step Tutorial For Beginners

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  • 170 pages
  • 6 hours of reading

More about the book

Build your own Neural Network today with easy-to-follow instructions and examples that cover the fundamentals of deep learning. You'll learn to create your own Neural Network in Python using TensorFlow, Keras, PyTorch, and Theano, all for a fraction of the cost of traditional textbooks. The book aims to deepen your understanding of deep learning, guide you in setting up your coding environment, and help you progress from a beginner to a professional. It is designed for complete novices, those looking to enhance their Python skills for deep learning, educators seeking effective teaching methods, and students focused on programming, neural networks, machine learning, and deep learning. To get started, you need Python 3.X, TensorFlow, Keras, and PyTorch installed on your computer. The author provides guidance on installing the necessary Python libraries. Inside, you'll find an overview of deep learning, artificial neural networks, library exploration, installation and setup, and basics of TensorFlow, Keras, and PyTorch. The book includes chapters on creating Convolutional and Recurrent Neural Networks. Written in accessible language, it minimizes complex math to cater to beginners. Each chapter features unique Neural Network architectures, along with Python code snippets and explanations to clarify the code's functionality, supplemented by screenshots of expected outputs. After reading, you'll be equipped to build your own

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Python Deep Learning, Samuel Burns

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Released
2019
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Title
Python Deep Learning
Subtitle
Develop Your First Neural Network In Python Using TensorFlow, Keras, And PyTorch - Step-by-Step Tutorial For Beginners
Language
English
Released
2019
Format
Paperback
Pages
170
ISBN10
1092562222
ISBN13
9781092562225
Series
Description
Build your own Neural Network today with easy-to-follow instructions and examples that cover the fundamentals of deep learning. You'll learn to create your own Neural Network in Python using TensorFlow, Keras, PyTorch, and Theano, all for a fraction of the cost of traditional textbooks. The book aims to deepen your understanding of deep learning, guide you in setting up your coding environment, and help you progress from a beginner to a professional. It is designed for complete novices, those looking to enhance their Python skills for deep learning, educators seeking effective teaching methods, and students focused on programming, neural networks, machine learning, and deep learning. To get started, you need Python 3.X, TensorFlow, Keras, and PyTorch installed on your computer. The author provides guidance on installing the necessary Python libraries. Inside, you'll find an overview of deep learning, artificial neural networks, library exploration, installation and setup, and basics of TensorFlow, Keras, and PyTorch. The book includes chapters on creating Convolutional and Recurrent Neural Networks. Written in accessible language, it minimizes complex math to cater to beginners. Each chapter features unique Neural Network architectures, along with Python code snippets and explanations to clarify the code's functionality, supplemented by screenshots of expected outputs. After reading, you'll be equipped to build your own