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Machine Learning with TensorFlow 1.x

You're reading from Machine Learning with TensorFlow 1.x Second generation machine learning with Google's brainchild - TensorFlow 1.x

Product type Paperback

Published in Nov 2017

Publisher Packt

ISBN-13 9781786462961

Length 304 pages

Edition 1st Edition

Languages

Python

Tools

TensorFlow

Concepts

Machine Learning

Authors (3):

Hua

Ahmed

Ul Azeem

View More author details

Table of Contents (19) Chapters

Title Page

Credits

About the Authors

About the Reviewer

www.PacktPub.com

Customer Feedback

Preface

1. Getting Started with TensorFlow FREE CHAPTER

2. Your First Classifier

3. The TensorFlow Toolbox

4. Cats and Dogs

5. Sequence to Sequence Models-Parlez-vous Français?

6. Finding Meaning

7. Making Money with Machine Learning

8. The Doctor Will See You Now

9. Cruise Control - Automation

10. Go Live and Go Big

11. Going Further - 21 Problems

12. Advanced Installation

Additional setup

The next part will focus on image processing and manipulation. This requires some extra libraries you may not have. At this point, it may make sense to just install all the typical packages required in scientific computing, which can be done as follows:

sudo apt-get install python-numpy python-scipy python-matplotlib 
ipython ipython-notebook python-pandas python-sympy python-nose

Additionally, install the image processing library, some external matrix mathematics libraries, and underlying requirements, which can be done as follows:

sudo pip install ndimagesudo apt-get install libatlas3-base-dev gcc gfortran g++

Converting images to matrices

Much of machine learning is just operations on matrices. We will start that process next by converting our images into a series of matrices—essentially, a 3D matrix as wide as the number of images we have.

Almost all matrix operations that we will perform in this chapter, and the entire book, use NumPy—the most popular scientific computing...

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Authors (3)

Hua

Hua

Quan Hua is a Computer Vision and Machine Learning Engineer at BodiData, a data platform for body measurements, where he focuses on developing computer vision and machine learning applications for a handheld technology capable of acquiring a body avatar while a person is fully clothed. He earned a bachelor of science degree from the University of Science, Vietnam, specializing in Computer Vision. He has been working in the field of computer vision and machine learning for about 3 years at start-ups. Quan has been writing for Packt since 2015 for a Computer Vision book, OpenCV 3 Blueprints.

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Ahmed

Ahmed

Saif Ahmed is an accomplished quantitative analyst and data scientist with 15 years of industry experience. His career started in management consulting at Accenture and lead him to quantitative and senior management roles at Goldman Sachs and AIG Investments. Most recently, he co-founded and runs a start-up focused on applying Deep Learning to automating medical imaging. He obtained his bachelor's degree in computer science from Cornell University and is currently pursuing a graduate degree in data science at U.C. Berkeley.

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Ul Azeem

Ul Azeem

Shams Ul Azeem is an undergraduate in electrical engineering from NUST Islamabad, Pakistan. He has a great interest in the computer science field, and he started his journey with Android development. Now, hes pursuing his career in Machine Learning, particularly in deep learning, by doing medical-related freelancing projects with different companies. He was also a member of the RISE lab, NUST, and he has a publication credit at the IEEE International Conference, ROBIO as a co-author of Designing of motions for humanoid goalkeeper robots.

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