Dan Toomey - Learning Jupyter
Here you can read online Dan Toomey - Learning Jupyter full text of the book (entire story) in english for free. Download pdf and epub, get meaning, cover and reviews about this ebook. year: 2016, publisher: Packt Publishing, genre: Computer. Description of the work, (preface) as well as reviews are available. Best literature library LitArk.com created for fans of good reading and offers a wide selection of genres:
Romance novel
Science fiction
Adventure
Detective
Science
History
Home and family
Prose
Art
Politics
Computer
Non-fiction
Religion
Business
Children
Humor
Choose a favorite category and find really read worthwhile books. Enjoy immersion in the world of imagination, feel the emotions of the characters or learn something new for yourself, make an fascinating discovery.
- Book:Learning Jupyter
- Author:
- Publisher:Packt Publishing
- Genre:
- Year:2016
- Rating:4 / 5
- Favourites:Add to favourites
- Your mark:
Learning Jupyter: summary, description and annotation
We offer to read an annotation, description, summary or preface (depends on what the author of the book "Learning Jupyter" wrote himself). If you haven't found the necessary information about the book — write in the comments, we will try to find it.
- Learn to write, execute, and comment your live code and formulae all under one roof using this unique guide
- This one-stop solution on Project Jupyter will teach you everything you need to know to perform scientific computation with ease
- This easy-to-follow, highly practical guide lets you forget your worries in scientific application development by leveraging big data tools such as Apache Spark, Python, R etc
Jupyter Notebook is a web-based environment that enables interactive computing in notebook documents. It allows you to create and share documents that contain live code, equations, visualizations, and explanatory text. The Jupyter Notebook system is extensively used in domains such as data cleaning and transformation, numerical simulation, statistical modeling, machine learning, and much more.
This book starts with a detailed overview of the Jupyter Notebook system and its installation in different environments. Next well help you will learn to integrate Jupyter system with different programming languages such as R, Python, JavaScript, and Julia and explore the various versions and packages that are compatible with the Notebook system. Moving ahead, you master interactive widgets, namespaces, and working with Jupyter in a multiuser mode.
Towards the end, you will use Jupyter with a big data set and will apply all the functionalities learned throughout the book.
What you will learn- Install and run the Jupyter Notebook system on your machine
- Implement programming languages such as R, Python, Julia, and JavaScript with Jupyter Notebook
- Use interactive widgets to manipulate and visualize data in real time
- Start sharing your Notebook with colleagues
- Invite your colleagues to work with you in the same Notebook
- Organize your Notebook using Jupyter namespaces
- Access big data in Jupyter
Dan Toomey has been developing applications for over 20 years. He has worked in a variety of industries and size companies in roles from sole contributor to VP/CTO level. For the last 10 years or so, he has been contracting to companies in the eastern Massachusetts area. Dan has been contracting under Dan Toomey Software Corp. Again, as a contractor developer in the area. Dan has also written R for Data Sciences with Packt Publishing.
Table of Contents- Introduction to Jupyter
- Jupyter Python Scripting
- Jupyter R Scripting
- Jupyter Julia Scripting
- Jupyter JavaScript Coding
- Interactive Widgets
- Sharing and Converting Jupyter Notebooks
- Multiuser Jupyter Notebooks
- Jupyter Scala
- Jupyter and Big Data
Dan Toomey: author's other books
Who wrote Learning Jupyter? Find out the surname, the name of the author of the book and a list of all author's works by series.
![Dan Toomey [Dan Toomey] - Jupyter for Data Science](/uploads/posts/book/119624/thumbs/dan-toomey-dan-toomey-jupyter-for-data-science.jpg)
![Joshua Cook [Joshua Cook] - Docker for Data Science: Building Scalable and Extensible Data Infrastructure Around the Jupyter Notebook Server](/uploads/posts/book/119616/thumbs/joshua-cook-joshua-cook-docker-for-data.jpg)
Learning Jupyter — read online for free the complete book (whole text) full work
Below is the text of the book, divided by pages. System saving the place of the last page read, allows you to conveniently read the book "Learning Jupyter" online for free, without having to search again every time where you left off. Put a bookmark, and you can go to the page where you finished reading at any time.
Font size:
Interval:
Bookmark:
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: November 2016
Production reference: 1241116
Published by Packt Publishing Ltd.
Livery Place
35 Livery Street
Birmingham
B3 2PB, UK.
ISBN 978-1-78588-487-0
www.packtpub.com
Author Dan Toomey | Copy Editors Vikrant Phadke Safis Editing |
Reviewer Jesse Bacon | Project Coordinator Nidhi Joshi |
Commissioning Editor Veena Pagare | Proofreader Safis Editing |
Acquisition Editor Manish Nainani | Indexer Mariammal Chettiyar |
Content Development Editor Aishwarya Pandere | Graphics Disha Haria |
Technical Editor Prasad Ramesh | Production Coordinator Nilesh Mohite |
Dan Toomey has been developing applications for over 20 years. He has worked in a variety of industries and size companies in roles from sole contributor to VP/CTO level. For the last 10 years or so, he has been contracting to companies in the eastern Massachusetts area. Dan has been contracting under Dan Toomey Software Corp. Again, as a contractor developer in the area. Dan has also written R for Data Sciences with Packt Publishing.
Jesse Bacon is a hobbyist programmer and technologist in the Washington D.C. metro area. In his free time, he mostly works through a new title about an interesting technology or spends time at the gym. Mr. Bacon values the opinions of the development community and looks forward to a new generation of programmers with all the gifts of today's computing environments.
For support files and downloads related to your book, please visit www.PacktPub.com .
Did you know that Packt offers eBook versions of every book published, with PDF and ePub files available? You can upgrade to the eBook version at www.PacktPub.com and as a print book customer, you are entitled to a discount on the eBook copy. Get in touch with us at service@packtpub.com for more details.
At www.PacktPub.com , you can also read a collection of free technical articles, sign up for a range of free newsletters and receive exclusive discounts and offers on Packt books and eBooks.
https://www.packtpub.com/mapt
Get the most in-demand software skills with Mapt. Mapt gives you full access to all Packt books and video courses, as well as industry-leading tools to help you plan your personal development and advance your career.
- Fully searchable across every book published by Packt
- Copy and paste, print, and bookmark content
- On demand and accessible via a web browser
Learning Jupyter discusses using Jupyter to record your scripts and results for a data analysis project. Jupyter allows the data scientist to record their complete analysis process, much in the same way other scientists use a lab notebook for recording tests, progress, results and conclusions. Jupyter works in a variety of operating systems and the book covers the use of Jupyter in Windows and Mac OS X along with the various steps necessary to enable your specific needs. Jupyter supports a variety of scripting languages by the addition of language engines so the user can portray their script natively in it.
, Introduction to Jupyter , takes a first look at the Jupyter user interface, walks through installing Jupyter on Windows and Mac OS X, examines the basic operations of Jupyter Notebook available through the user interface for all engines, and gives an overview of the security features available and configuration options.
, Jupyter Python Scripting , walks through a simple Python notebook and the underlying structure. This chapter also shows an example of using pandas, graphics, and using random numbers in a Python script.
, Jupyter R Scripting , adds the ability to use R scripts in your Jupyter Notebook, adds an R library not included in the standard R installation, makes a Hello World script in R, and shows R data access against built-in libraries and some of the simpler graphics and statistics that are automatically generated. We use an R script to generate 3D graphics in a couple of different ways, perform a cluster analysis, and use one of the forecasting tools available in R.
, Jupyter Julia Scripting , adds the ability to use Julia scripts in your Jupyter Notebook, adds a Julia library not included in the standard Julia installation, and shows the basic features of Julia. We outline some of the limitations encountered with using Julia in Jupyter and display graphics using some of the graphics packages available, including Gadfly, Winston, Vega, and Pyplot. We show parallel processing in action, a small control flow example, and how to add unit testing to your Julia script.
, Jupyter JavaScript Coding , shows how to add JavaScript to a Jupyter Notebook, some of the limitations of using Javascript in Jupyter and examples of several packages that are exemplary of Node.js coding, including d3 for graphics, stats-analysis for statistics, built-in JSON handling, Canvas for creating graphics files and Plotly used for generating graphics with a third-party tool. You learn how multi-threaded applications can be developed using Node.js under Jupyter and use machine learning to develop a decision tree.
, Interactive Widgets, adds widgets to our Jupyter installation , uses interact and interactive widgets to produce a variety of user input controls. We explain the widgets package in depth to investigate the user controls available, properties available in the containers, and events that are available emitting from the controls. You will see how to build containers of controls.
Font size:
Interval:
Bookmark:
Similar books «Learning Jupyter»
Look at similar books to Learning Jupyter. We have selected literature similar in name and meaning in the hope of providing readers with more options to find new, interesting, not yet read works.
Discussion, reviews of the book Learning Jupyter and just readers' own opinions. Leave your comments, write what you think about the work, its meaning or the main characters. Specify what exactly you liked and what you didn't like, and why you think so.