Book Image

Julia Cookbook

By : Raj R Jalem, Jalem Raj Rohit
Book Image

Julia Cookbook

By: Raj R Jalem, Jalem Raj Rohit

Overview of this book

Want to handle everything that Julia can throw at you and get the most of it every day? This practical guide to programming with Julia for performing numerical computation will make you more productive and able work with data more efficiently. The book starts with the main features of Julia to help you quickly refresh your knowledge of functions, modules, and arrays. We’ll also show you how to utilize the Julia language to identify, retrieve, and transform data sets so you can perform data analysis and data manipulation. Later on, you’ll see how to optimize data science programs with parallel computing and memory allocation. You’ll get familiar with the concepts of package development and networking to solve numerical problems using the Julia platform. This book includes recipes on identifying and classifying data science problems, data modelling, data analysis, data manipulation, meta-programming, multidimensional arrays, and parallel computing. By the end of the book, you will acquire the skills to work more effectively with your data.

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Julia Cookbook
Raj R Jalem | Jalem Raj Rohit
Sep, 2016 | 172 pages
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Table of Contents (12 chapters)
Julia Cookbook
Julia Cookbook
Credits
Credits
About the Author
About the Author
About the Reviewer
About the Reviewer
www.PacktPub.com
www.PacktPub.com
Preface
Preface
Free Chapter
1
Extracting and Handling Data
Extracting and Handling Data
Introduction
Why should we use Julia for data science?
Handling data with CSV files
Handling data with TSV files
Working with databases in Julia
Interacting with the Web
2
Metaprogramming
Metaprogramming
Introduction
Representation of a Julia program
Symbols and expressions
Symbols
Quoting
Interpolation
The Eval function
Macros
Metaprogramming with DataFrames
3
Statistics with Julia
Statistics with Julia
Introduction
Basic statistics concepts
Descriptive statistics
Deviation metrics
Sampling
Correlation analysis
4
Building Data Science Models
Building Data Science Models
Introduction
Dimensionality reduction
Linear discriminant analysis
Data preprocessing
Linear regression
Classification
Performance evaluation and model selection
Cross validation
Distances
Distributions
Time series analysis
5
Working with Visualizations
Working with Visualizations
Introduction
Plotting basic arrays
Plotting dataframes
Plotting functions
Exploratory data analytics through plots
Line plots
Scatter plots
Histograms
Aesthetic customizations
6
Parallel Computing
Parallel Computing
Introduction
Basic concepts of parallel computing
Data movement
Parallel maps and loop operations
Channels

Julia Cookbook

Copyright © 2016 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

First published: September 2016

Production reference: 1260916

Published by Packt Publishing Ltd. 

Livery Place 

35 Livery Street

Birmingham B3 2PB, UK.

ISBN 978-1-78588-201-2

www.packtpub.com

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