Learning Jupyter 5 – Second Edition: Interactive computing across Python, Java, JavaScript, R & Julia

Write code, mathematics, graphics, and output, all in a single document, as well as in a web browser with JupyterKey FeaturesGet acquainted with Jupyter 5.x and its newest features such as cell tagging, keyboard shortcuts, attractive tables styles and more.Leverage big data tools such as Apache Spark and explore datasets with pandas, scikit-learn and TensorFlow.Explore JupyterHub and start creating a multi-user Hub which manages and proxies multiple instances of the single-user Jupyter notebook server.Book DescriptionJupyter 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, you will learn to integrate Jupyter system with different programming languages such as R, Python, Java, 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.By the end, you will use Jupyter with a big data set and will apply all the functionalities learned throughout the book. You will learn all about Jupyter notebook and start performing data transformation, numerical simulation, data visualization and much more interactively.What you will learnInstall and run the Jupyter Notebook system on your machineImplement programming languages such as R, Python, Julia, and JavaScript with Jupyter NotebookUse interactive widgets to manipulate and visualize data in real timeStart sharing your Notebook with colleaguesInvite your colleagues to work with you in the same NotebookOrganize your Notebook using Jupyter namespacesAccess big data in JupyterWho This Book Is ForThis book target all developers, data scientist, machine learning users and all those who are working on data analysis or data science projects across different teams. Data science professionals will also find this book very useful to perform technical and scientific computing collaboratively.

Author: Dan Toomey

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