What we're about
Upcoming events (1)
Link visible for attendees
One common obstacle to getting Machine Learning projects off the ground is “analysis paralysis”: data scientists can get stuck in the very early stages of development selecting the right approaches, algorithms, and applications that will lead to actionable results and trustworthy decision making. In many instances, new initiatives have aspects that are similar to other, existing projects, so having access to a catalog of fully built-out ML model-based applications will enable new development to leverage solutions that have already proven their effectiveness.
Applied ML Prototypes (AMPs), pioneered by researchers at Fast Forward Labs, provide Data Scientists with open source pre-built reference examples and end-to-end solutions, using some of the most cutting edge ML methods, for a variety of common data science projects. AMPs enable data scientists to go from an idea to a fully working ML use case in a fraction of the time.
In this Meetup, Jake Bengtson from Cloudera will demonstrate how the AMP Churn Modeling with scikit learn can be repurposed to create a web application that will predict this year’s NBA champion. Jake will walk through the entire process of transforming this AMP, from ingesting historical NBA data, to altering the existing Flask application to use a newly trained model.
About the speaker
Jake is currently leading technical product marketing for ML Lifecycle products at Cloudera. Before joining Cloudera, Jake worked as a Data Scientist and then as a Data Science and Analytics Solution Architect at ExxonMobil. Additionally, he worked as a Senior Data Scientist at FarmersEdge. Before starting his professional career, Jake obtained his bachelor’s and master’s degree from Brigham Young University. When he isn’t working, Jake enjoys skiing, golfing, and spending time with his family in the mountains.
This is still a tricky time for public gatherings, but Future of Data is committed to providing great tech content & facilitating discussions in the Machine Learning space. Our group in Austin, Texas is holding this event; in order to do our part to fight the spread of COVID-19's Omicron variant, this will be an exclusively online event originating in Central Daylight Time (the event time displayed on this page will reflect the equivalent local time). We thought it might be of interest to our wider membership (you are welcome to sign up for it here).