by Dan Toomey | Released March 2017 | ISBN: 9781788299176

Learn how to write code, mathematics, graphics, and output, all in a single document and in a web browser, using Project Jupyter About This VideoWrite, execute, and comment your live code and formulae under one roof using this unique tutorial.This one-stop solution will teach you everything you need to know about Project Jupyter to perform scientific computation with ease.This easy-to-follow, highly practical video facilitates scientific application development by leveraging big data tools such as Apache Spark, Python, R, and more.In DetailJupyter 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 tutorial starts with a detailed overview of the Jupyter Notebook system and its installation in different environments. Next you will learn to integrate the Jupyter system with different programming languages such as R, Python, JavaScript, and Julia; further, you'll explore the various versions and packages that are compatible with the Notebook system. Moving ahead, you'll master interactive widgets, namespaces, and working with Jupyter in multiuser mode. Towards the end, you will use Jupyter with a big dataset and will apply all the functionalities learned throughout the video. Show and hide more

1. Chapter 1 : Introduction to Jupyter
   • The Course Overview 00:03:41
   • First Look at Jupyter 00:04:38
   • Installing Jupyter on Windows 00:02:56
   • Installing Jupyter on Mac 00:00:47
   • Notebook Structure, Workflow, andBasic Operations 00:10:52
   • Security and Configuration Operations in Jupyter 00:03:28
2. Chapter 2 : Jupyter Python scripting
   • Basic Python in Jupyter 00:04:12
   • Python Data Access in Jupyter 00:02:10
   • Python pandas in Jupyter 00:01:44
   • Python Graphics in Jupyter 00:01:51
   • Python Random Numbers in Jupyter 00:01:16
3. Chapter 3 : Jupyter R scripting
   • Adding R Scripting to Your Installation 00:04:33
   • Basic R in Jupyter 00:02:03
   • R Dataset Access and Visualization in Jupyter 00:03:01
   • R Cluster Analysis and Forecasting 00:03:12
4. Chapter 4 : Jupyter Julia Scripting
   • Adding Julia Scripting to Your Installation 00:03:21
   • Basic Julia in Jupyter 00:02:43
   • Julia Limitations and Standard Capabilities 00:02:34
   • Julia Visualizations in Jupyter 00:01:51
   • Julia Vega Plotting and Parallel Processing 00:02:35
   • Julia Control Flow, Regular Expressions, and Unit Testing 00:04:34
5. Chapter 5 : Jupyter JavaScript Coding
   • Adding JavaScript Scripting to Your Installation 00:02:30
   • JavaScript Hello World Jupyter Notebook 00:02:14
   • Basic JavaScript in Jupyter 00:02:16
   • Node.js stats-analysis Package and JSON Handling 00:02:25
   • Node.js plotly Package 00:01:50
   • Node.js Asynchronous Threads 00:01:33
   • Node.js decision-tree Package 00:02:35
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