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Deep Learning with TensorFlow

Deep Learning with TensorFlow

By : Zaccone, Karim
3 (4)
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Deep Learning with TensorFlow

Deep Learning with TensorFlow

3 (4)
By: Zaccone, Karim

Overview of this book

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.
Table of Contents (13 chapters)
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12
Index

The TensorFlow GPU setup


To use TensorFlow with NVIDIA GPUs, the first step is to install the CUDA Toolkit.

Once the CUDA Toolkit is installed, you must download the cuDNN v5.1 library for Linux from https://developer.nvidia.com/cudnn.

cuDNN is a library that helps accelerate deep learning frameworks, such as TensorFlow and Theano. Here's a brief explanation from the NVIDIA website:

"The NVIDIA CUDA® Deep Neural Network library (cuDNN) is a GPU-accelerated library of primitives for deep neural networks. cuDNN provides highly tuned implementations for standard routines such as forward and backward convolution, pooling, normalization, and activation layers. cuDNN is part of the NVIDIA Deep Learning SDK."

Before installing it, you'll need to register on NVIDIA's Accelerated Computing Developer Program. Once you're registered, log in and download cuDNN 5.1 to your local computer.

Once it is downloaded, decompress the files and copy...

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