Use a Jupyter Notebook for machine learning and data science interviews

Create and edit files, generate charts, and create models

With Jupyter Notebooks, interviewers and candidates can configure and arrange workflows in data science, scientific computing, computational journalism, and machine learning.

To use the feature in an interview, select Jupyter from the language dropdown:

With our Jupyter Notebook feature, you can leverage big data tools, such as Apache Spark, from Python, R, and Scala and explore that same data with pandas, scikit-learn, ggplot2, and TensorFlow, all within the interview experience. 

This is great for conducting live machine learning or data science interviews where you might need to aggregate data from multiple CSV's, create charts and models, and collaborate on different programs.