Book Image

Learning Jupyter

By : Dan Toomey
Book Image

Learning Jupyter

By: Dan Toomey

Overview of this book

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 we’ll 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.
Table of Contents (16 chapters)
Learning Jupyter
About the Author
About the Reviewer

Node.js decision-tree package

The decision-tree package is an example of a machine learning package. It is available at . The package is installed using the following command:

npm install decision-tree

We need a dataset to use for training/developing our decision tree. I am using the car MPG dataset on this page: . It did not seem to be available directly, so I copied it into Excel and saved it as a local CSV.

The logic for machine learning is very similar:

  • Load our dataset

  • Split into a training set and a testing set

  • Use the training set to develop our model

  • Test the mode on the test set.


Typically, you might use two-thirds of your data for training and one-third for testing.

Using the decision-tree package and the car MPG dataset we would have a script similar to the following:

//Import the modules
var DecisionTree = require('decision-tree');
var fs = require("fs");...