This tutorial is part of the Getting started with Watson Studio learning path.
Introduction to IBM Watson Studio
Data visualization, preparation, and transformation using IBM Watson Studio
Automate model building in IBM Watson Studio
Creating SPSS Modeler flows in IBM Watson Studio
Build models using Jupyter Notebooks in IBM Watson Studio
This tutorial explains how to set up and run Jupyter Notebooks from within IBM® Watson Studio. We start with a data set for customer churn that is available on Kaggle. The data set has a corresponding Customer Churn Analysis Jupyter Notebook (originally developed by Sandip Datta), which shows the archetypical steps in developing a machine learning model by going through the following essential steps:
Import the data set.
Analyze the data by creating visualizations and inspecting basic statistic parameters (for example, mean or standard variation).
Prepare the data for machine model building (for example, by transforming categorical features into numeric features and by normalizing the data).
Split the data
Original URL: https://developer.ibm.com/tutorials/watson-studio-using-jupyter-notebook/