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Machine Learning for Developers

You're reading from Machine Learning for Developers

Product type Book

Published in Oct 2017

Publisher Packt

ISBN-13 9781786469878

Pages 270 pages

Edition 1st Edition

Languages

Concepts

Machine Learning

Authors (2):

Rodolfo Bonnin

Md Mahmudul Hasan

View More author details

Table of Contents (10) Chapters

Preface

Introduction - Machine Learning and Statistical Science

The Learning Process

Clustering

Linear and Logistic Regression

Neural Networks

Convolutional Neural Networks

Recurrent Neural Networks

Recent Models and Developments

Software Installation and Configuration

Linux installation

Linux is, in our view, the most flexible platform on which you can work for machine learning projects. As you probably know, there is a really large number of alternatives in the Linux realm, and they all have their own particular package management.

Given that writing instructions for working on all these distributions would take a large number of pages, we will settle on instructions for the Ubuntu 16.04 distribution.

Ubuntu is undoubtedly the most widespread Linux distribution, and in the particular case of Ubuntu 16.04 it is an LTS version, or long term support. This means that the base software we will run in this book will have support until the year 2021.

You will find more information about the meaning of LTS at https://wiki.ubuntu.com/LTS.

Regarding the feasibility of Ubuntu as a scientific computing distribution, even if it is considered by many to...

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Authors (2)

Rodolfo 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.

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