Google Cloud AI for March Madness

I was up at 2:00 am this morning, Spring Break…no idea why, and since I was awake decided to work on my March Madness basketball bracket.

While researching free-throw percentages, defensive efficiency and strength of schedule I was excited to find a new tool marketed by Google Cloud.

At first glance it’s an interesting way to create/customize an algorithm for SMEs (subject matter experts) without requiring assistance from engineers or data scientists.

There must have been an issue with the tool because I kept receiving this “Technical Foul” message.

However, I wanted to share because it’s a very interesting use-case for how an engineer and data scientist can create a tool for thousands of people to create their own algorithm without ever writing a single line of code.

Here’s a post on the topic from Alison Wagonfeld – Chief Marketing Officer, Google Cloud.

“In connection with this year’s March Madness tournament, we’re extending our NCAA campaign to developers everywhere with training that enables anyone with an interest in basketball and data analytics to dive in.  More and more developers want to use Google Cloud, and we are ready to meet that demand. (In fact, a recent study by Indeed found that Google Cloud skills are the fastest cloud skills growing in demand.)

We’ve published a new series of Qwiklabs training to teach you how to use BigQuery to analyze NCAA basketball data with SQL and build a machine learning model to make your own predictions. At Google Cloud Next on April 9-11 (right after the Final Four), we’ll be hosting two bootcamps (Sunday and Monday) that use NCAA data to show you how to build a data science environment covering ingest, exploration, training, evaluation, deployment, and prediction. We’re co-hosting a predictive modeling competition with Kaggle that lets data scientists show their chops (and compete to win $10,000!). And we’ve published a technical blog post and a whitepaper to give you a deeper look under the hood.”

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