DataHour: Create Effective Data Science Notebooks and Communication

Being able to clearly communicate your process and findings is an important, yet underrated skill for data scientists and machine learning practitioners. Engaging and accessible notebooks are the perfect way to combine your big picture presentations with a varying amount of code for more technical audiences. Built around well-designed data visuals, the ideal notebook captures the attention of its readers through masterful storytelling and important insights.

In this DataHour, Martin will share some tips and best practices for effective data science communication. Notebooks can play a powerful role at any step of the machine learning and data science workflow, and allow you to communicate and improve your work all the way from data ingestion to the final model or actionable insights. Moreover, these notebooks can serve as a reproducible documentation of your work and reduce technical debt. This DataHour will cover all those aspects, and give recommendations on how to design impactful notebooks according to your needs.

Prerequisites: Enthusiasm for learning Data Science!

Martin has a Ph.D. in Astrophysics from Technical University Munich and currently works as a Data Scientist at YipitData. He has extensive experience in data wrangling, EDA, and data visualization in Python & R; and is passionate about storytelling and communication.He is one of the top members of the Kaggle community as the first ever Kernels Grandmaster, and former number 1 in the Notebooks ranking, with 23 gold medals to his name. His granular level documentation is well lauded within the community. In addition, he is a Discussions Grandmaster with 108 Gold Medals.