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Deep Learning with TensorFlow

You're reading from  Deep Learning with TensorFlow

Product type Book
Published in Apr 2017
Publisher Packt
ISBN-13 9781786469786
Pages 320 pages
Edition 1st Edition
Languages
Authors (3):
Giancarlo Zaccone Giancarlo Zaccone
Profile icon Giancarlo Zaccone
Md. Rezaul Karim Md. Rezaul Karim
Profile icon Md. Rezaul Karim
Ahmed Menshawy Ahmed Menshawy
Profile icon Ahmed Menshawy
View More author details

Table of Contents (11) Chapters

Preface Getting Started with Deep Learning First Look at TensorFlow Using TensorFlow on a Feed-Forward Neural Network TensorFlow on a Convolutional Neural Network Optimizing TensorFlow Autoencoders Recurrent Neural Networks GPU Computing Advanced TensorFlow Programming Advanced Multimedia Programming with TensorFlow Reinforcement Learning

Requirements for running TensorFlow with GPU from NVIDIA

The GPU-enabled version of TensorFlow has several requirements such as 64-bit Linux, Python 2.7 (or 3.3+ for Python 3), NVIDIA CUDA 7.5 (CUDA 8.0 required for Pascal GPUs) and NVIDIA, cuDNN v4.0 (minimum) or v5.1 (recommended). More specifically, the current development of TensorFlow supports only GPU computing using NVIDIA toolkits and software. Now the following software must be installed on your machine.

Step 1: Install NVIDIA CUDA

To use TensorFlow with NVIDIA GPUs, CUDA Toolkit 8.0 and associated NVIDIA drivers with CUDA Toolkit 8+ need to be installed.

For more details, refer to this NVIDIA's documentation
https://developer.nvidia.com/cuda-downloads.

Now download and install the required package from...

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