Jupyter Notebooks are awesome but there are so many. Just at Google we have Colab, Kaggle Notebooks, and Cloud AI Platform Notebooks. So which should you use? The answer is “it depends”. This session will summarize your options and try to help you choose the best notebook for your needs.
Check out this informative and well designed summary of election simulations from the consistently great Nate Silver and fivethirtyeight.com.
Check out this cool visualization from The Pudding. It’s an interactive map of the most viewed people pages on wikipedia keyed by number of views and arranged by locations that person is connected with.
Very well executed analysis of the data on trending YouTube videos:
In this article we’ll build a simple yet powerful short link service using two of my favorite Google Cloud technologies: Cloud Run and Firestore. The code can be found on Github and here’s a slide version of this story.
This is the second of a two part series in which we focus on interesting queries and visualizations using the data pipeline we created in part one.
What’s bigger than Wikipedia? Spoiler: Wikipedia page views. This is the first of a two part series in which we’ll explore how to build a data engineering solution to process all 10TB of published wikipedia pageviews and entity data.
One easy way to get your data into the cloud, quickly and inexpensively (free actually!).