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You're reading from Deep Learning By Example A hands-on guide to implementing advanced machine learning algorithms and neural networks

Product type Paperback

Published in Feb 2018

Publisher Packt

ISBN-13 9781788399906

Length 450 pages

Edition 1st Edition

Languages

Python

Tools

Keras

Concepts

Deep Learning

Author (1):

Menshawy

View More author details

Table of Contents (23) Chapters

Title Page

Packt Upsell

Contributors

Preface

1. Data Science - A Birds' Eye View FREE CHAPTER

2. Data Modeling in Action - The Titanic Example

3. Feature Engineering and Model Complexity – The Titanic Example Revisited

4. Get Up and Running with TensorFlow

5. TensorFlow in Action - Some Basic Examples

6. Deep Feed-forward Neural Networks - Implementing Digit Classification

7. Introduction to Convolutional Neural Networks

8. Object Detection – CIFAR-10 Example

9. Object Detection – Transfer Learning with CNNs

10. Recurrent-Type Neural Networks - Language Modeling

11. Representation Learning - Implementing Word Embeddings

12. Neural Sentiment Analysis

13. Autoencoders – Feature Extraction and Denoising

14. Generative Adversarial Networks

15. Face Generation and Handling Missing Labels

16. Implementing Fish Recognition

Code for fish recognition

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Index

TensorFlow installation

TensorFlow installation comes with two modes: CPU and GPU. We will start off the installation tutorial by installing TensorFlow in GPU mode.

TensorFlow GPU installation for Ubuntu 16.04

The GPU mode installation of TensorFlow requires an up-to-date installation of the NVIDIA drivers because the GPU version of TensorFlow only supports CUDA at the moment. The following section will take you through a step-by-step process of installing NVIDIA drivers and CUDA 8.

Installing NVIDIA drivers and CUDA 8

First off, you need to install the correct NVIDIA driver based on your GPU. I have a GeForce GTX 960M GPU, so I will go ahead and install nvidia-375 (if you have a different GPU, you can use the NVIDIA search tool http://www.nvidia.com/Download/index.aspx to help you find your correct driver version). If you want to know your machine's GPU, you can issue the following command in the terminal: