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You're reading from  Julia Cookbook

Product typeBook
Published inSep 2016
Reading LevelBeginner
Publisher
ISBN-139781785882012
Edition1st Edition
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Authors (2):
Jalem Raj Rohit
Jalem Raj Rohit
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Jalem Raj Rohit

Jalem Raj Rohit is an IIT Jodhpur graduate with a keen interest in recommender systems, machine learning, and serverless and distributed systems. Raj currently works as a senior consultantdata scienceand NLP at Episource, before which he worked at Zomato and Kayako. He contributes to open source projects in Python, Go, and Julia. He also speaks at tech conferences about serverless engineering and machine learning.
Read more about Jalem Raj Rohit

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Preface

Julia is a programming language that promises both speed and support for extensive data science applications. Apart from the official documentation of the language, and the individual documentations for each package, there is no single resource that combines all of them and provides a detailed guide to carry out machine learning and data science. So, this book aims to solve the problem by being a comprehensive guide to learning data science for a Julia programmer, right from the exploratory analytics part to the visualization part.

What this book covers

Chapter 1, Extracting and Handling Data, deals with the importance of the Julia programming language for data science and its applications. It also serves as a guide to handle data in the most available formats, and shows how to crawl and scrape data from the Internet.

Chapter 2, Metaprogramming, covers the concept of metaprogramming, where a language can express its own code as a data structure of itself. For example, Lisp expresses code in the form of Lisp arrays, which are data structures in Lisp itself. Similarly, Julia can express its code as data structures.

Chapter 3, Statistics with Julia, teaches you how to perform statistics in Julia, along with the common problems of handling data arrays, distributions, estimation, and sampling techniques.

Chapter 4, Building Data Science Models, talks about various data science and statistical models. You will learn to design, customize, and apply them to various data science problems. This chapter will also teach you about model selection and the ways to learn how to build and understand robust statistical models.

Chapter 5, Working with Visualizations, teaches you how to visualize and present data, and also to analyze and the findings from the data science approach that you have taken to solve a particular problem. There are various types of visualizations to display your findings, namely the bar plot, the scatter plot, pie chart, and so on. It is very important to choose an appropriate method that can reflect your findings and work in a sensible and an aesthetically pleasing manner.

Chapter 6, Parallel Computing, talks about the concepts of parallel computing and handling a lot of data in Julia.

What you need for this book

A beginner level proficiency in the Julia programming language and experience with any programming language, preferably dynamically typed ones such as Python. The software requirements assume you have any of the following OSes: Linux, Windows, or OS X. There are no specific hardware requirements, except that you run and work all your code on a desktop, or a laptop preferably.

Who this book is for

This book is for beginner-level programmers, preferably Julia programmers who are looking to explore and learn the concepts in the domain of data science.

Sections

In this book, you will find several headings that appear frequently (Getting ready, How to do it…, How it works…, There's more…, and See also).

To give clear instructions on how to complete a recipe, we use these sections as follows:

Getting ready

This section tells you what to expect in the recipe, and describes how to set up any software or any preliminary settings required for the recipe.

How to do it…

This section contains the steps required to follow the recipe.

How it works…

This section usually consists of a detailed explanation of what happened in the previous section.

There's more…

This section consists of additional information about the recipe in order to make the reader more knowledgeable about the recipe.

See also

This section provides helpful links to other useful information for the recipe.

Conventions

In this book, you will find a number of text styles that distinguish between different kinds of information. Here are some examples of these styles and an explanation of their meaning. Code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles are shown as follows: "The DataFrames package is needed to deal with TSV files."

Any command-line input or output is written as follows:

query = """ CREATE TABLE Student
      (
         ID INT NOT NULL AUTO_INCREMENT,
         Name VARCHAR(255),
         Attendance FLOAT,
         JoinDate DATE,
         Enrolments INT,
         PRIMARY KEY (ID)
     );"""

New terms and important words are shown in bold. Words that you see on the screen, for example, in menus or dialog boxes, appear in the text like this: "If we check the page, we should see our Page rendered! alert logged to the console."

Note

Warnings or important notes appear in a box like this.

Tip

Tips and tricks appear like this.

Reader feedback

Feedback from our readers is always welcome. Let us know what you think about this book—what you liked or disliked. Reader feedback is important for us as it helps us develop titles that you will really get the most out of.

To send us general feedback, simply e-mail feedback@packtpub.com, and mention the book's title in the subject of your message.

If there is a topic that you have expertise in and you are interested in either writing or contributing to a book, see our author guide at www.packtpub.com/authors.

Customer support

Now that you are the proud owner of a Packt book, we have a number of things to help you to get the most from your purchase.

Errata

Although we have taken every care to ensure the accuracy of our content, mistakes do happen. If you find a mistake in one of our books—maybe a mistake in the text or the code—we would be grateful if you could report this to us. By doing so, you can save other readers from frustration and help us improve subsequent versions of this book. If you find any errata, please report them by visiting http://www.packtpub.com/submit-errata, selecting your book, clicking on the Errata Submission Form link, and entering the details of your errata. Once your errata are verified, your submission will be accepted and the errata will be uploaded to our website or added to any list of existing errata under the Errata section of that title.

To view the previously submitted errata, go to https://www.packtpub.com/books/content/support and enter the name of the book in the search field. The required information will appear under the Errata section.

Piracy

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Please contact us at copyright@packtpub.com with a link to the suspected pirated material.

We appreciate your help in protecting our authors and our ability to bring you valuable content.

Questions

If you have a problem with any aspect of this book, you can contact us at questions@packtpub.com, and we will do our best to address the problem.

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Published in: Sep 2016Publisher: ISBN-13: 9781785882012
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Authors (2)

author image
Jalem Raj Rohit

Jalem Raj Rohit is an IIT Jodhpur graduate with a keen interest in recommender systems, machine learning, and serverless and distributed systems. Raj currently works as a senior consultantdata scienceand NLP at Episource, before which he worked at Zomato and Kayako. He contributes to open source projects in Python, Go, and Julia. He also speaks at tech conferences about serverless engineering and machine learning.
Read more about Jalem Raj Rohit