Data
Reader small image

You're reading from  Machine Learning for Developers

Product typeBook
Published inOct 2017
Reading LevelBeginner
PublisherPackt
ISBN-139781786469878
Edition1st Edition
Languages
Python
Tools
SciPyScikit-learn
Concepts
Machine Learning
Right arrow
Authors (2):
Rodolfo Bonnin
Rodolfo Bonnin
author image
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.
Read more about Rodolfo Bonnin

Md Mahmudul Hasan
Md Mahmudul Hasan
author image
Md Mahmudul Hasan


Read more about Md Mahmudul Hasan

View More author details
Right arrow

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...

lock icon
The rest of the page is locked
Previous Page
Chapter 10 of 10, Page 2
Next Page
You have been reading a chapter from
Machine Learning for Developers
Published in: Oct 2017Publisher: PacktISBN-13: 9781786469878
© 2017 Packt Publishing Limited All Rights Reserved

Authors (2)

author image
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.
Read more about Rodolfo Bonnin

author image
Md Mahmudul Hasan


Read more about Md Mahmudul Hasan

Other recommended products

Related to this chapter

AI Crash Course

AI Crash Course

AI legend Hadelin de Ponteves captures his proven AI training approach in a friendly, interactive, and hands-on tutorial book.

BookNov 2019360 pages5
AI Crash Course

AI Crash Course

AI legend Hadelin de Ponteves captures his proven AI training approach in a friendly, interactive, and hands-on tutorial book.

BookNov 2019360 pages5
TensorFlow 1.x Deep Learning Cookbook

TensorFlow 1.x Deep Learning Cookbook

Deep Neural Networks (DNNs) have achieved a lot of success in the field of computer vision, speech recognition, and natural language processing. In this book, you will learn how to efficiently use TensorFlow, Google's open source framework for deep learning, and implement different deep learning networks with easy to follow independent recipes.

BookDec 2017536 pages
Python Data Mining Quick Start Guide

Python Data Mining Quick Start Guide

This book is an introduction to data mining and its practical demonstration of working with real-world data sets. With this book, you will be able to extract useful insights using common Python libraries. You will also learn key stages like data loading, cleaning, analysis, visualization to build an efficient data mining pipeline.

BookApr 2019188 pages
SciPy Recipes

SciPy Recipes

The SciPy stack is a popular Python ecosystem used for mathematical and scientific computing tasks. Learn how you can put to use the various functionalities offered by the SciPy stack in the most efficient way possible. With the help of this book, you will solve real-world problems in linear algebra, numerical analysis, visualization, and more.

BookDec 2017386 pages
Deep Learning with Keras

Deep Learning with Keras

Keras is a high-level neural network library written in Python that runs on top of either Theano or TensorFlow. With this book, you’ll learn the basics of Keras in a highly practical way and understand how this minimal, highly modular framework runs on both CPU and GPU, allowing you to put your ideas into action in the shortest possible time.

BookApr 2017318 pages
Practical Convolutional Neural Networks

Practical Convolutional Neural Networks

This book helps you master CNN, from the basics to the most advanced concepts in CNN such as GANs, instance classification and attention mechanism for vision models and more. You will implement advanced CNN models using complex image and video datasets. By the end of the book you will learn CNN’s best practices to implement smart ConvNet models and apply them to solve complex deep learning problems.

BookFeb 2018218 pages
Mastering Numerical Computing with NumPy

Mastering Numerical Computing with NumPy

Mastering Numerical Computing with Python guides you in performing complex computing with cutting-edge coverage on advanced concepts such as exploratory data analysis and clustering algorithms. You'll become an expert in addressing matrix calculations, and write efficient NumPy codes for implementing algorithms with real-world examples.

BookJun 2018248 pages
Hands-On Deep Learning Architectures with Python

Hands-On Deep Learning Architectures with Python

This book explains the essential learning algorithms used for deep and shallow architectures. Packed with practical implementations to help you understand the concepts and ideas required to build efficient artificial intelligence systems, this book will help you construct deep models using popular frameworks and datasets.

BookApr 2019316 pages
R Deep Learning Essentials

R Deep Learning Essentials

This book demonstrates how to use deep Learning in R for machine learning, image classification, and natural language processing. It covers topics such as convolutional networks, recurrent neural networks, transfer learning and deep learning in the cloud. By the end of this book, you will be able to apply deep learning to real-world projects.

BookAug 2018378 pages
Hands-On Artificial Intelligence for IoT

Hands-On Artificial Intelligence for IoT

The book will help you get well-versed with different techniques in Artificial Intelligence such as machine learning, deep learning, natural language processing and more to build smart IoT systems. By the end of the book, you will have practical knowledge on how to implement and manipulate text, audio, and speech data within the IoT system.

BookJan 2019390 pages
Hands-On Generative Adversarial Networks with Keras

Hands-On Generative Adversarial Networks with Keras

This book will explore deep learning and generative models, and their applications in artificial intelligence. You will learn to evaluate and improve your GAN models by eliminating challenges that are encountered in real-world applications. You will implement GAN architectures in various domains such as computer vision, NLP, and audio processing

BookMay 2019272 pages

Personalised recommendations for you

Based on your interests and search pattern

Et al.

Et al.

Ever wonder why speech recognition systems don't understand the Scottish accent, or what would happen if an astronaut only ate mac 'n' cheese, or other spurious reflections you'd have at a bar? We did, then collated those deliberations into absurd research articles with fake figures and methodologies inspired by even more fictionally absurd studies.

BookAug 2023230 pages5
Generative AI with LangChain

Generative AI with LangChain

This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.

BookDec 2023360 pages4
Generative AI with LangChain

Generative AI with LangChain

This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.

BookDec 2023360 pages5
Generative AI with LangChain

Generative AI with LangChain

This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.

BookDec 2023360 pages1
Generative AI with LangChain

Generative AI with LangChain

This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.

BookDec 2023360 pages5
Mastering Tableau 2023

Mastering Tableau 2023

This book is a comprehensive resource to mastering your Tableau skills and becoming a BI expert. As you progress, you will learn how to build advanced dashboards and improve your storytelling to derive key business insight, as well as make you well-versed with advanced functionalities of Tableau in the business intelligence domain.

BookAug 2023684 pages
Building AI Applications with ChatGPT APIs

Building AI Applications with ChatGPT APIs

This guide covers all ChatGPT API features for effortless creation of robust AI powered apps. With its help, you’ll be able to leverage ChatGPT’s cutting-edge NLP models to take your app development skills to the next level. You’ll also work on ten exciting projects that will give you the practical know-how that you can apply to your existing applications.

BookSep 2023258 pages5
Building AI Applications with ChatGPT APIs

Building AI Applications with ChatGPT APIs

This guide covers all ChatGPT API features for effortless creation of robust AI powered apps. With its help, you’ll be able to leverage ChatGPT’s cutting-edge NLP models to take your app development skills to the next level. You’ll also work on ten exciting projects that will give you the practical know-how that you can apply to your existing applications.

BookSep 2023258 pages2
Data Engineering with AWS

Data Engineering with AWS

Embark on a journey to master data engineering pipelines on AWS! Our book offers a hands-on experience of AWS services for ingesting, transforming, and consuming data. Whether you're an absolute beginner or someone with basic data engineering experience, this guide is an indispensable resource.

BookOct 2023636 pages5
Modern Data Architecture on AWS

Modern Data Architecture on AWS

Every organization wants an agile, performant, and cost-effective data platform that meets all their current and future business needs. Purpose-built AWS analytics services and their features play a big part in building such a modern data platform. This book brings to you all the design and architectural patterns that’ll help you achieve this goal.

BookAug 2023420 pages5
Practical Guide to Applied Conformal Prediction in Python

Practical Guide to Applied Conformal Prediction in Python

Discover the power of Conformal Prediction with the "Practical Guide to Applied Conformal Prediction in Python." Master the latest techniques to quantify uncertainty in machine learning and computer vision models, and seamlessly apply them to your industry applications.

BookDec 2023240 pages
TinyML Cookbook

TinyML Cookbook

With over 70 project-based recipes, the TinyML Cookbook is a practical guide that will help you to get the most out of your microcontrollers. It provides a comprehensive understanding of the theoretical foundations while giving you hands-on experience training ML models for deployment on Arduino Nano 33 BLE Sense, Raspberry Pi Pico, and SparkFun RedBoard Artemis Nano microcontrollers.

BookNov 2023664 pages