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Machine Learning for Developers

You're reading from Machine Learning for Developers Uplift your regular applications with the power of statistics, analytics, and machine learning

Product type Paperback

Published in Oct 2017

Publisher Packt

ISBN-13 9781786469878

Length 270 pages

Edition 1st Edition

Languages

Python

Tools

Scikit-learn

Concepts

Machine Learning

Authors (2):

Bonnin

Hasan

View More author details

Table of Contents (17) Chapters

Title Page

Credits

Foreword

About the Author

About the Reviewers

www.PacktPub.com

Customer Feedback

Preface

1. Introduction - Machine Learning and Statistical Science FREE CHAPTER

2. The Learning Process

3. Clustering

4. Linear and Logistic Regression

5. Neural Networks

6. Convolutional Neural Networks

7. Recurrent Neural Networks

8. Recent Models and Developments

9. Software Installation and Configuration

macOS X environment installation

Now it's the turn of macOS X installation. The installation process is very similar to Linux, and is based on the OS X High Sierra edition.

Note

The installation requires sudo privileges for the installing user.

Anaconda installation

Anaconda can be installed via a graphical installer or a console-based one. In this section, we will cover the graphical installer. First, we will download the installer package from https://www.anaconda.com/download/ and choose the 64-bit package:

Once we have downloaded the installer package, we execute the installer, and we are presented with the step-by-step GUI:

Then, we choose the installation location (take into account that the whole package needs almost 2 GB of disk to install):

Firstly, we accept the license, before actually installing all the required files:

After the necessary processes of file decompression and installing, we are ready to start using the Anaconda utilities:

A last step will be to install the missing packages...

The rest of the chapter is locked

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Authors (2)

Bonnin

Bonnin

Rodolfo Bonnin is a systems engineer and Ph.D. student at Universidad Tecnolgica Nacional, Argentina. He has also pursued parallel programming and image understanding postgraduate courses at Universitt Stuttgart, Germany. He has been doing research on high-performance computing since 2005 and began studying and implementing convolutional neural networks in 2008, writing a CPU- and GPU-supporting neural network feedforward stage. More recently he's been working in the field of fraud pattern detection with Neural Networks and is currently working on signal classification using machine learning techniques. He is also the author of Building Machine Learning Projects with Tensorflow and Machine Learning for Developers by Packt Publishing.

See other products by Bonnin

Hasan

Hasan

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